Ckan MCP Server vs Codescene MCP Server
A side-by-side look at the Ckan MCP Server and Codescene MCP Server MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Ckan MCP Server for developer tools work as a local process; choose Codescene MCP Server for developer tools as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Ckan MCP Server when
- You need dedicated capabilities in the Developer Tools domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
ckan_package_search, ckan_find_relevant_datasets, ckan_package_show.
Choose Codescene MCP Server when
- You need dedicated capabilities in the Developer Tools domain.
- You prefer a local stdio subprocess transport.
- You want tools like
analyze_change_set, code_health_refactoring_business_case, code_health_review.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Developer Tools | Developer Tools |
| Quality signal | 68/100 · Great | 65/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | No auth required | Not declared |
| Pricing | Free | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 60 | 71 |
| Directory activity | 1 views 0 installs 0 upvotes | 3 views 0 installs 0 upvotes |
| Tools | 20 | 28 |
| Full listing | View Ckan MCP Server | View Codescene MCP Server |
Tools & capabilities
Ckan MCP Server tools 20
ckan_package_searchSearch for datasets (packages) on a CKAN server using Solr query syntax. Supports full Solr search capabilities including filters, facets, and sorting. Use this to discover datasets matching specific criteria. Note on parser behavior: Some CKAN portals use a restrictive default query parser that can break long OR queries. For those portals, this tool may force the query into 'text:(...)' based on per-portal config. You can override with 'query_parser' to force or disable this behavior per request. Important - Date field semantics: - issued: publisher's content publish date when available (best proxy for "created/published") - modified: publisher's content update date when available - metadata_created: CKAN record creation timestamp (publish time on source portals, harvest time on aggregators; fallback for "created" if issued missing) - metadata_modified: CKAN record update timestamp (publish time on source portals, harvest time on aggregators; use for "updated/modified in last X") Natural language mapping (important for tool callers): - "created"/"published" -> prefer issued; fallback to metadata_created - "updated"/"modified" -> prefer modified; fallback to metadata_modified - For "recent in last X", consider using content_recent (issued with metadata_created fallback) Content-recent helper: - content_recent: if true, rewrites the query to use issued with a fallback to metadata_created when issued is missing. - content_recent_days: window for content_recent (default 30 days). Args: - server_url (string): Base URL of CKAN server (e.g., "https://dati.gov.it/opendata") - q (string): Search query using Solr syntax (default: "*:*" for all) - fq (string): Filter query (e.g., "organization:comune-palermo") IMPORTANT — Solr fq syntax rules: 1. OR inside a single field: use field:(val1 OR val2), NOT field:val1 OR field:val2. Wrong: fq=type:"A" OR type:"B" → silently ignored, returns entire catalog. Right: fq=type:("A" OR "B") 2. CKAN extras fields are indexed as extras_fieldname, not fieldname. e.g. to filter on extra field "hvd_category" use fq=extras_hvd_category:"<value>" - rows (number): Number of results to return (default: 10, max: 1000) - start (number): Offset for pagination (default: 0) - page (number): Page number (1-based); alias for start. Overrides start if provided. - page_size (number): Results per page when using page (default: 10, max: 1000) - sort (string): Sort field and direction (e.g., "metadata_modified desc") - facet_field (array): Fields to facet on (e.g., ["organization", "tags"]) - facet_limit (number): Max facet values per field (default: 50) - include_drafts (boolean): Include draft datasets (default: false) - query_parser ('default' | 'text'): Override search parser behavior - response_format ('markdown' | 'json'): Output format Returns: Search results with: - count: Number of results found - results: Array of dataset objects - facets: Facet counts (if facet_field specified) - search_facets: Detailed facet information Query Syntax (parameter q): Boolean operators: - AND / &&: "water AND climate" - OR / ||: "health OR sanità" - NOT / !: "data NOT personal" - +required -excluded: "+title:water -title:sea" - Grouping: "(title:water OR title:climate) AND tags:environment" Wildcards: - *: "title:environment*" (matches environmental, environments, etc.) - Note: Left truncation (*water) not supported Fuzzy search (edit distance): - ~: "title:rest~" or "title:rest~1" (finds "test", "best", "rest") Proximity search (words within N positions): - "phrase"~N: "title:"climate change"~5" Range queries: - Inclusive [a TO b]: "num_resources:[5 TO 10]" - Exclusive {a TO b}: "num_resources:{0 TO 100}" - One side open: "metadata_modified:[2024-01-01T00:00:00Z TO *]" Date math: - NOW-1YEAR, NOW-6MONTHS, NOW-7DAYS, NOW-1HOUR - NOW/DAY, NOW/MONTH (round down) - Combined: "metadata_modified:[NOW-2MONTHS TO NOW]" - Example: "metadata_created:[NOW-1YEAR TO *]" - IMPORTANT: NOW syntax works on metadata_modified and metadata_created fields - For 'modified' and 'issued' fields, NOW syntax is auto-converted to ISO dates - Manual ISO dates always work: "modified:[2026-01-15T00:00:00Z TO *]" Field existence: - Exists: "field:*" or "field:[* TO *]" - Not exists: "NOT field:*" or "-field:*" Boosting (relevance scoring): - Boost term: "title:water^2 OR notes:water" (title matches score higher) - Constant score: "title:water^=1.5" Examples: - Search all: { q: "*:*" } - By tag: { q: "tags:sanità" } - Boolean: { q: "(title:water OR title:climate) AND NOT title:sea" } - Wildcard: { q: "title:environment*" } - Fuzzy: { q: "title:health~2" } - Proximity: { q: "notes:"open data"~3" } - Date range: { q: "metadata_modified:[2024-01-01T00:00:00Z TO 2024-12-31T23:59:59Z]" } - Date math: { q: "metadata_modified:[NOW-6MONTHS TO *]" } - Date math (auto-converted): { q: "modified:[NOW-30DAYS TO NOW]" } - Published in 2025 (content date): { fq: "issued:[2025-01-01T00:00:00Z TO 2025-12-31T23:59:59Z]" } - First appeared on portal in 2025: { fq: "metadata_created:[2025-01-01T00:00:00Z TO 2025-12-31T23:59:59Z]" } - Recent content (issued w/ fallback): { q: "*:*", content_recent: true, content_recent_days: 180 } - Field exists: { q: "organization:* AND num_resources:[1 TO *]" } - Boosting: { q: "title:climate^2 OR notes:climate" } - Filter org: { fq: "organization:regione-siciliana" } - Filter extras field (correct): { fq: "extras_hvd_category:"http://data.europa.eu/bna/c_ac64a52d"" } - Filter extras OR (correct): { fq: "extras_hvd_category:("http://data.europa.eu/bna/c_ac64a52d" OR "http://data.europa.eu/bna/c_dd313021")" } - Get facets: { facet_field: ["organization"], rows: 0 } Query language: Before searching a portal, check its locale via ckan_status_show (field: "Portal Locale" / locale_default). Translate query terms to the portal's language — searching in English on a non-English portal returns 0 results. Examples: locale "it" → Italian terms; "uk_UA" → Ukrainian (Cyrillic); "fr_FR" → French. Exception: multilingual portals (e.g. data.europa.eu, open.canada.ca) accept EN + native terms joined with OR. Typical workflow: ckan_status_show (check locale) → ckan_package_search (query in portal's language) → ckan_package_show (get full metadata + resource IDs) → ckan_datastore_search (query tabular data)ckan_find_relevant_datasetsFind and rank datasets by relevance to a query using weighted fields. Use this instead of ckan_package_search when you want relevance-ranked results with explicit scoring across title, notes, tags, and organization fields. Use ckan_package_search instead when you need Solr filter syntax, facets, or pagination. Uses package_search for discovery and applies a local scoring model. Args: - server_url (string): Base URL of CKAN server (e.g., "https://dati.gov.it/opendata") - query (string): Natural language or keyword query (e.g., "mobilità urbana", "air quality") - limit (number): Number of datasets to return (default: 10) - weights (object): Field weights for scoring — higher weight = more influence on rank Default: title=4, tags=3, notes=2, organization=1, holder=4, publisher=2, coverage=4 coverage: bonus for datasets the portal returned with every query term required (Solr mm=100%); these are fetched first, the rest fills in when they are fewer than limit Note on holder vs organization: on federated catalogs (e.g. dati.gov.it), `organization` is the harvesting catalog (e.g. Regione Puglia), while `holder` (DCAT-AP_IT dct:rightsHolder) is the actual data owner (e.g. Comune di Lecce). Queries like "datasets from a specific Comune" match `holder` correctly; matching only `organization` misses datasets harvested via aggregators. `publisher` (dct:publisher) is scored separately at lower weight as it can contain technical roles ("Redazione OD") rather than the institutional owner. - query_parser ('default' | 'text'): Override search parser behavior - response_format ('markdown' | 'json'): Output format Returns: Ranked datasets with relevance scores and per-field score breakdowns Examples: - { server_url: "https://dati.gov.it/opendata", query: "mobilità" } - { server_url: "...", query: "trasporti", limit: 5, weights: { title: 5, notes: 2 } } - { server_url: "...", query: "defibrillatori Comune di Lecce", weights: { holder: 5 } } Typical workflow: ckan_find_relevant_datasets → ckan_package_show (inspect top results) → ckan_datastore_search (query data)ckan_package_showGet complete metadata for a specific dataset (package). Returns full details including resources, organization, tags, and all metadata fields. Notes: - metadata_modified is a CKAN record timestamp (publish time on source portals, harvest time on aggregators), not the content date. - issued/modified are content dates when provided by the publisher. - JSON output adds metadata_harvested_at (same as metadata_modified). Args: - server_url (string): Base URL of CKAN server - id (string): Dataset ID or name (machine-readable slug) - include_tracking (boolean): Include view/download statistics (default: false) - response_format ('markdown' | 'json'): Output format Returns (JSON format): id, name, title, notes, organization, tags, state, license_title, metadata_created, metadata_modified, issued, modified, author, maintainer, frequency, language, publisher_name, holder_name, hvd_category, applicable_legislation, temporal_coverage (array of {start, end, start_equals_issued} from dct:temporal; empty if absent; start_equals_issued=true when start = issued and no end: on dcatapit portals an export default, not a data period), resources (id, name, format, url, size, datastore_active, created, last_modified, api_json_url), view_url, api_json_url Examples: - { server_url: "https://dati.gov.it/opendata", id: "dataset-name" } - { server_url: "...", id: "abc-123-def", include_tracking: true } Typical workflow: ckan_package_show → pick a resource with datastore_active=true → ckan_datastore_search (query its data)ckan_list_resourcesList all resources in a dataset with a compact summary. Returns a focused table of resources showing format, size, DataStore availability, and download URL. Use this to quickly assess what files a dataset contains before deciding how to access the data. Args: - server_url (string): Base URL of CKAN server - id (string): Dataset ID or name - format_filter (string): Filter resources by format, case-insensitive (e.g., "CSV", "json", "XLSX") - response_format ('markdown' | 'json'): Output format Returns: Compact resource summary with name, ID, format, size, DataStore flag, and URL Examples: - { server_url: "https://dati.gov.it/opendata", id: "dataset-name" } - { server_url: "...", id: "dataset-name", format_filter: "CSV" } Typical workflow: ckan_package_search → ckan_list_resources (assess available files) → ckan_datastore_search (for resources with DataStore=true) When a resource has DataStore=false but its download URL belongs to a different (source) portal, the tool can probe the source portal for DataStore availability and report source_datastore_active and source_portal_url so you can query the data there instead. This probing is OFF by default (it issues extra HTTP requests to hosts taken from the dataset's own resource URLs); set check_source_portal=true to enable it.ckan_organization_listList all organizations on a CKAN server. Organizations are entities that publish and manage datasets. Args: - server_url (string): Base URL of CKAN server - all_fields (boolean): Return full objects vs just names (default: false) - sort (string): Sort field (default: "name asc") - limit (number): Maximum results (default: 100). Use 0 to get only the count via faceting - offset (number): Pagination offset (default: 0) - response_format ('markdown' | 'json'): Output format Returns: List of organizations with metadata. When limit=0, returns only the count of organizations with datasets. Typical workflow: ckan_organization_list → ckan_organization_show (inspect one) → ckan_package_search with fq="organization:name" (browse its datasets)ckan_organization_showGet details of a specific organization. Args: - server_url (string): Base URL of CKAN server - id (string): Organization ID or name - include_datasets (boolean): Include list of datasets (default: true) - include_users (boolean): Include list of users (default: false) - response_format ('markdown' | 'json'): Output format Returns: Organization details with optional datasets and users Typical workflow: ckan_organization_show → ckan_package_show (inspect a dataset) → ckan_datastore_search (query its data)ckan_organization_searchSearch for organizations by name pattern. This tool provides a simpler interface than package_search for finding organizations. Wildcards are automatically added around the search pattern. Args: - server_url (string): Base URL of CKAN server - pattern (string): Search pattern (e.g., "toscana", "salute") - response_format ('markdown' | 'json'): Output format Returns: List of matching organizations with dataset counts Examples: - { server_url: "https://www.dati.gov.it/opendata", pattern: "toscana" } - { server_url: "https://open.canada.ca/data", pattern: "health" } Typical workflow: ckan_organization_search → ckan_organization_show (get details) → ckan_package_search with fq="organization:name"ckan_datastore_searchQuery data from a CKAN DataStore resource. The DataStore allows SQL-like queries on tabular data. Not all resources have DataStore enabled. The response always includes a Fields section listing all available column names and types. Use limit=0 to discover column names without fetching data — do this before using filters to avoid guessing column names and getting HTTP 400 errors. Args: - server_url (string): Base URL of CKAN server - resource_id (string): ID of the DataStore resource - q (string): Full-text search query (optional) - filters (object): Key-value filters (e.g., { "anno": 2023 }) - limit (number): Max rows to return (default: 100, max: 32000) - offset (number): Pagination offset (default: 0) - fields (array): Specific fields to return (optional) - sort (string): Sort field with direction (e.g., "anno desc") - distinct (boolean): Return distinct values (default: false) - response_format ('markdown' | 'json'): Output format Returns: DataStore records matching query, always including available column names and types Examples: - { server_url: "...", resource_id: "abc-123", limit: 0 } ← discover columns first - { server_url: "...", resource_id: "abc-123", limit: 50 } - { server_url: "...", resource_id: "...", filters: { "regione": "Sicilia" } } - { server_url: "...", resource_id: "...", sort: "anno desc", limit: 100 } Typical workflow: ckan_package_search → ckan_package_show (find resource_id with datastore_active=true) → ckan_datastore_search (limit=0 to get columns) → ckan_datastore_search (with filters)ckan_datastore_search_sqlRun SQL queries on a CKAN DataStore resource. This endpoint is only available on CKAN portals with DataStore enabled and SQL access exposed. Args: - server_url (string): Base URL of CKAN server - sql (string): SQL query (e.g., SELECT * FROM "resource_id" LIMIT 10) - response_format ('markdown' | 'json'): Output format Returns: SQL query results from DataStore Examples: - { server_url: "...", sql: "SELECT * FROM "abc-123" LIMIT 10" } - { server_url: "...", sql: "SELECT COUNT(*) AS total FROM "abc-123"" } Typical workflow: ckan_package_show (get resource_id) → ckan_datastore_search_sql (run SQL on it) Security note: SQL queries are forwarded directly to the CKAN DataStore API. The CKAN server enforces its own access controls and read-only permissions. No local database is exposed. Queries are limited to public DataStore resources on the target portal.ckan_status_showCheck if a CKAN server is available and get version information. Useful to verify server accessibility before making other requests. Also shows the count of High-Value Datasets (HVD) when the portal supports it. Args: - server_url (string): Base URL of CKAN server Returns: Server status, version information, and HVD dataset count (if available) Typical workflow: ckan_status_show (verify server is up) → ckan_package_search (discover datasets)ckan_tag_listList tags from a CKAN server using faceting. This returns tag names with counts, optionally filtered by dataset query or tag substring. Args: - server_url (string): Base URL of CKAN server - q (string): Dataset search query (default: "*:*") - fq (string): Filter query (optional) - tag_query (string): Filter tags by substring (optional) - limit (number): Max tags to return (default: 100, max: 1000) - response_format ('markdown' | 'json'): Output format Returns: List of tags with counts (from faceting) Typical workflow: ckan_tag_list → ckan_package_search with fq="tags:tag_name" (find datasets by tag) → ckan_package_showckan_group_listList all groups on a CKAN server. Groups are thematic collections of datasets. Args: - server_url (string): Base URL of CKAN server - all_fields (boolean): Return full objects vs just names (default: false) - sort (string): Sort field (default: "name asc") - limit (number): Maximum results (default: 100). Use 0 to get only the count via faceting - offset (number): Pagination offset (default: 0) - response_format ('markdown' | 'json'): Output format Returns: List of groups with metadata. When limit=0, returns only the count of groups with datasets. Typical workflow: ckan_group_list → ckan_group_show (inspect one) → ckan_package_search with fq="groups:name" (browse its datasets)- +8 more on the listing page
Codescene MCP Server tools 28
analyze_change_setRun a branch-level Code Health review for all files that differ between current HEAD and base_ref. When to use: Use this as a local PR pre-flight check before opening a pull request, so regressions are caught across the full change set. Limitations: - Requires a valid git repository path. - base_ref must exist and be resolvable by git in that repository. - Reviews only files that differ from base_ref. - Output is JSON text from the CLI command. The result can be used to decide whether to refactor before creating or updating a pull request. Returns: A JSON object containing: - quality_gates: the central outcome, summarizing whether the change set passes or fails Code Health thresholds ("passed" or "failed"). - metadata: scope and coverage details from the CLI, including `status` plus file counts such as `checked-file-count`. Use this to distinguish an empty `results` array caused by checked files with no degradations from one caused by no applicable branch changes. - results: an array of objects for each affected file with: - name: the name of the file whose Code Health is impacted. - verdict: "improved", "degraded", "stable", or "unknown". - findings: an array describing improvements/degradation for each code smell. Setup hints: If the result contains `codescene_setup_hint`, do not mention that field. Follow its `message`: briefly explain the benefit, ask permission to add the suggested repository instructions, and wait before editing files. On failure: If this tool returns an error (e.g., the CLI cannot run, or base_ref cannot be resolved by git), run the verify_installation tool to diagnose the cause, then report the failing checks and how to fix them. Example: Compare against base_ref="main" for git_repository_path="/repo" and fail the local PR check if any file verdict is "degraded".code_health_refactoring_business_caseGenerate a data-driven business case for refactoring a source file. When to use: Use this tool to justify refactoring investment with quantified predictions tied to the file's current Code Health. Limitations: - Estimates are model-based projections, not guarantees. - Evaluates one file at a time. - Requires an analyzable source file. Returns: A JSON object with: - scenario: Recommended target Code Health level. - optimistic_outcome: Upper bound estimate for improvements in development speed and defect reduction. - pessimistic_outcome: Lower bound estimate for improvements. - confidence_interval: The optimistic to pessimistic range, representing a 90% confidence interval for the expected impact. On failure: If this tool returns an error (e.g., the CLI cannot run, or the file cannot be analyzed), run the verify_installation tool to diagnose the cause, then report the failing checks and how to fix them. Example: Call with file_path="/repo/src/service.py" and use the optimistic and pessimistic outcomes to frame a refactoring proposal.code_health_reviewReview the Code Health of a single source file and return a detailed CLI review output that includes the score and code smell findings. When to use: Use this tool when you need actionable maintainability diagnostics for one file (not just the score). Limitations: - Analyzes one file at a time. - Requires a supported source file. - Returns CLI review text, not a normalized JSON schema. Returns: A review string from the CodeScene CLI. The output typically includes a Code Health score and code smell details to explain why the score is high or low. The Code Health scores are interpreted as: * Optimal Code: a Code Health 10.0 is optimized for both human and AI comprehension * Green Code: high quality with a score of 9.0-9.9 * Yellow Code: problematic technical debt with a score of 4.0-8.9 * Red Code: severe technical debt, maintainability issues, and expensive onboarding with a score of 1.0-3.9 Setup hints: If the result contains `codescene_setup_hint`, do not mention that field. Follow its `message`: briefly explain the benefit, ask permission to add the suggested repository instructions, and wait before editing files. On failure: If this tool returns an error (e.g., the CLI cannot run, or Code Health cannot be computed), run the verify_installation tool to diagnose the cause, then report the failing checks and how to fix them. Example: Call with file_path="/repo/src/app.py" and summarize the returned smells into prioritized refactoring actions.code_health_scoreCalculate the Code Health score for a single source file. The tool returns one numeric score from 10.0 (optimal) to 1.0 (worst). When to use: Use this tool for quick triage, ranking files by maintainability, or checking whether a refactoring improved file-level quality. Limitations: - Analyzes one file at a time. - Returns only the score summary, not the full smell breakdown. - Requires a supported source file. Returns: A string in the format "Code Health score: <score>". The Code Health scores are interpreted as: * Optimal Code: Code Health 10.0 optimized for human and AI comprehension * Green Code: high quality with a score of 9.0-9.9 * Yellow Code: problematic technical debt with a score of 4.0-8.9 * Red Code: severe technical debt with a score of 1.0-3.9 On failure: If this tool returns an error (e.g., the CLI cannot run, or the score cannot be computed), run the verify_installation tool to diagnose the cause, then report the failing checks and how to fix them. Example: Call with file_path="/repo/src/module.py" and compare the score before and after a refactoring.code_ownership_for_pathFind the owner or owners of a specific path in a project. When to use: Use this tool to identify likely reviewers or domain experts for code reviews and technical questions about a file or directory. Limitations: - Requires a valid project_id. - Uses the latest project analysis data available in CodeScene. - If no matching ownership data is found, an empty JSON array is returned. Returns: A list of owners and their paths that they own. The name of the owner who can be responsible for code reviews or inquiries about the file and a link to the CodeScene System Map page filtered by the owner. Explain that this link can be used to see more details about the owner's contributions and interactions within the project. You MUST always show a link after every owner. Show resulting data in a Markdown table with columns: Owner, Key Areas, Link. On failure: If this tool returns an error (e.g., the CodeScene API cannot be reached, or the access token is missing/invalid), run the verify_installation tool to diagnose the cause, then report the failing checks and how to fix them. Example: Call with project_id=42 and path="/repo/src/service.py", then present each owner row with its corresponding system-map link.download_skillDownload a single skill to a local directory. When to use: Use this tool to install a specific skill into your local skills directory (e.g., ~/.claude/skills/). Limitations: - By default, refuses to overwrite existing skills. - Set overwrite=true to replace an existing skill. - Creates the destination directory if it does not exist. Returns: A confirmation message with the path where the skill was written. Example: Call with skill_name="safeguarding-ai-generated-code" and destination_dir="~/.claude/skills" to install the skill.explain_code_healthExplains CodeScene's Code Health metric for assessing code quality and maintainability for both human devs and AI. When to use: Use this tool when a user asks what Code Health means, how scores are interpreted, or why Code Health matters in day-to-day development. Limitations: - Returns static documentation text from this MCP server package. - Does not analyze a specific repository or file. Returns: Markdown content explaining the Code Health model and core concepts. Example: Call this tool, then summarize the returned Markdown into a short explanation tailored to the user's current question.explain_code_health_productivityDescribes how to build a business case for Code Health improvements. Covers empirical data on how healthy code lets you ship faster with fewer defects. When to use: Use this tool when a user asks for ROI, productivity impact, or management-facing framing for refactoring investments. Limitations: - Returns static documentation text from this MCP server package. - Does not compute project-specific forecasts. Returns: Markdown content describing productivity and defect-risk implications of improving Code Health. Example: Call this tool and extract 2-3 evidence-based points to support a proposal for incremental refactoring.get_configRead current CodeScene MCP Server configuration values. When to use: Use this tool to discover available configuration keys, inspect effective values, and understand where each value comes from. Limitations: - Returns JSON text only; callers must format it for display. - Sensitive values (tokens) are masked. - Effective values can be overridden by client-provided env vars. When called without a key, lists every available configuration option together with its current effective value, the source of that value (environment variable vs. config file), and a short description. When called with a specific key, returns details for that option only. Sensitive values (tokens) are masked in the output. Returns: A JSON string. When querying a single key, the object has: key, env_var, value, source, description, aliases, and docs_url. When listing all, the object has: config_dir and options (array of the same shape). Use the aliases array to match user intent to the correct key. Present the data clearly and always include docs_url links. Example: Call with key="access_token" to inspect one setting, or call without key to list all configurable options.get_skill_manifestGet the file manifest for a specific skill. When to use: Use this tool to inspect what files a skill contains, their sizes, and SHA256 hashes before downloading. Limitations: - Requires a valid skill name from list_skills. Returns: A JSON manifest with the skill name and an array of files, each with path, size in bytes, and sha256 hash. Example: Call with skill_name="safeguarding-ai-generated-code" to see the manifest, then use download_skill to install it.list_skillsList all available skills embedded in this MCP server. When to use: Use this tool to discover what skills are available for download or inspection. Limitations: - Returns only skills embedded at compile time. - Does not scan external skill directories. Returns: A formatted list of skill names with their descriptions. Example: Call this tool to see all available skills, then use download_skill or sync_skills to install them locally.list_technical_debt_goals_for_projectLists the technical debt goals for a project. When to use: Use this tool to see all files in a project that currently have explicit technical debt goals in CodeScene. Limitations: - Requires a valid project_id. - Returns goal data from the latest available analysis. - Includes only files with non-empty goals. Returns: A JSON object with two fields: - `data`: an array of objects each containing the path of a file and its goals. - `link`: a URL to the CodeScene Code Biomarkers page for the project. Show the goals for each file in a structured format that is easy to read and explain the goal description for each file. It also includes a description, please include that in your output. Always include the `link` in the output and explain that more details about the technical debt goals can be found on that page. On failure: If this tool returns an error (e.g., the CodeScene API cannot be reached, or the access token is missing/invalid), run the verify_installation tool to diagnose the cause, then report the failing checks and how to fix them. Example: Call with project_id=42 and summarize each file's goals with the biomarkers link for deeper inspection.- +16 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Ckan MCP Server
{
"mcpServers": {
"ckan-mcp-server": {
"command": "npx",
"args": [
"-y",
"@aborruso/ckan-mcp-server"
]
}
}
}
Codescene MCP Server
{
"mcpServers": {
"codescene-mcp-server": {
"command": "npx",
"args": [
"-y",
"@codescene/codehealth-mcp"
]
}
}
}
Frequently asked questions
Ckan MCP Server is categorized under Developer Tools and uses a local stdio subprocess. Codescene MCP Server belongs to Developer Tools and uses a local stdio subprocess. Pick Ckan MCP Server for developer tools work and Codescene MCP Server for developer tools.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Ckan MCP Server is listed as free. Auth: no auth required. Codescene MCP Server has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add ckan-mcp-server and codescene-mcp-server as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Ckan MCP Server has a quality signal of 68/100 (Great) with 1 views, 0 installs and 60 GitHub stars. Codescene MCP Server has 65/100 (Great) with 3 views, 0 installs and 71 GitHub stars.