Testdino MCP vs Ckan MCP Server
A side-by-side look at the Testdino MCP and Ckan 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 Testdino MCP for developer tools work as a local process; choose Ckan 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 Testdino MCP when
- You need dedicated capabilities in the Developer Tools domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
TESTDINO_PAT. - You want tools like
health, list_testruns, get_run_details.
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.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Developer Tools | Developer Tools |
| Quality signal | 65/100 · Great | 68/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | API key required | No auth required |
| Pricing | BYOK (pay the provider) | Free |
| Required env vars | TESTDINO_PAT | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 9 | 60 |
| Directory activity | 1 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 43 | 20 |
| Full listing | View Testdino MCP | View Ckan MCP Server |
Tools & capabilities
Testdino MCP tools 43
healthCheck if your TestDino connection is working. Verifies your PAT, shows your account information, and lists available organizations and projects. Each organization also shows your role in it (owner/admin/member/billing/viewer) so you can tell the user what they can do there — treat it as informational, not a security guarantee. Use this first to make sure everything is set up correctly and to get organization/project IDs for other tools.list_testrunsBrowse and filter your test runs to find specific test executions. Filter by git branch (e.g., 'develop', 'main'), run status ('passed', 'failed', 'interrupted', 'incomplete', 'running'), time interval ('Latest', '1h', '2h', '5h', '1d', '3d', '5d', 'weekly', 'monthly', or custom date ranges), commit author, environment (e.g., 'production', 'staging', 'development'), or test case tags. Search commit messages (or an exact run counter when numeric) with 'search', and order results with 'sort'. Supports efficient pagination using page/limit or offset/limit. Returns test run summaries with statistics (total, passed, failed, skipped, flaky counts), duration, status, branch, author, and PR information when available. Perfect for answering questions like 'What tests ran on the develop branch?' or 'Show me all failed runs from last hour.' The PAT should be configured in mcp.json as TESTDINO_PAT environment variable.get_run_detailsGet detailed information about test runs. Shows test statistics (passed, failed, skipped, flaky), all test suites and cases, git metadata, and error details. Supports batch operations (comma-separated IDs, max 20). Use this to analyze test execution health or debug specific failures. Set include_ai_insights=true (single testrun_id only) to also get the run's AI Insights under `ai_insights`: AI failure categorization (flaky/bug/ui_change), failure clusters, new-failures cards, the error-analysis table, and the LLM-written run summary. AI payloads are generated lazily — if `ai_insights` sections report status "processing"/"not_generated", poll get_ai_insights(testrun_id=...) until "completed" instead of re-calling this tool. An "unavailable" section carries the upstream statusCode: a 5xx or timeout is transient (retry once via get_ai_insights), a 4xx (bad ids) is terminal.list_testcaseList test cases with comprehensive filtering options. Provide a run scope: by_testrun_id or counter for specific runs, OR a cross-run filter (by_branch, by_time_interval, by_author, by_commit, by_environment, by_pages) which resolves the matching runs internally — you do NOT need to call list_testruns first. Without a run scope the tool returns an empty result with a warning explaining what to provide. Combine per-case filters (status, tags, runtime, artifacts, attempt number) with any run scope. page/limit paginate WITHIN the resolved run(s); limit is snapped to the nearest of 10, 25, 50, 100 (data-handler's allowed page sizes).get_testcase_detailsGet detailed information about a specific test case. You can identify the test case in two ways: 1) By testcase_id (can be used alone), or 2) By testcase_name combined with testrun_id (required because test cases can have the same name across different test runs). Returns error message, code snippet, file location, test steps per attempt, console logs, and artifacts (screenshots, videos, traces). Use steps_filter='failed_only' to return only steps that errored, stripping passing setup/hook steps. Use this to debug why a test failed or understand how it executed. Example: 'Get test case details for "Verify user can logout and login" in testrun #43'.debug_testcaseFetch historical execution and failure data for a specific test case. Returns raw historical data with test run details (ID, counter, branch), test runs summary, and a debugging prompt from the API. Each execution includes its associated test run information (testRunId, testRunCounter, branch) to help correlate failures across different test runs and branches. The AI client will analyze the data to identify failure patterns, find root causes, and provide fix suggestions. Use this when you need to debug a failing test case. Example: 'Debug test case "Verify user login"'. Set include_ai_insights=true to also get TestDino's stored AI analysis for this test under `ai_fixes`: recommendations (investigation/remediation steps + reasoning + historical insight) and quick fixes (concrete fixes, often with code snippets, plus long-term stabilization steps). By default they target the most recent failing execution; pass testrun_id to target a specific run. AI payloads are generated lazily — if `ai_fixes` sections report status "in_progress", poll get_ai_insights(testrun_id=..., testcase_id=...) until they report "completed". An "unavailable" section carries the upstream statusCode: a 5xx or timeout is transient (retry once via get_ai_insights); a 4xx (bad ids) is terminal.get_debug_evidenceStart every failing-test investigation here. One call returns the whole cheap tier of the evidence ladder: the computed flake verdict with its per-attempt failure signatures, the regression boundary (the last run this test passed and the first it failed), and download links for every stored artifact — trace, screenshots, and the expected/actual/diff images on a visual failure. Read all of it before forming a hypothesis. The verdict says whether the failure repeats, never why, so it rules fixes out rather than pointing at a cause; the boundary turns "why does this fail" into "what changed between these two runs", which is a far smaller question. Artifact links are minutes-scale: download what you need immediately, and call this again to mint fresh ones rather than treating an expired link as a missing artifact.get_flake_verdictSay whether a failing test behaves the same way every time, by comparing its retry attempts within one run. If you are debugging a failing test, call get_debug_evidence first — it returns this plus the regression boundary and every artifact link in one call, so calling this separately afterwards repeats work already done. Returns a computed verdict — "deterministic" (every attempt failed with the same signature, so the failure repeats), "flaky" (an attempt passed on retry, so the outcome is not consistent), or "inconclusive" (too few attempts, or the attempts failed differently) — plus the per-attempt signatures behind it. The verdict describes the behaviour, not the cause. It tells you which fixes the evidence cannot support; it does not tell you where the fix goes. Decide that after reading the artifacts, the trace and the code. Needs a test that ran with retries enabled; a single attempt is always inconclusive.verify_fixCheck whether a fix actually held for one test, against the run you saw when you proposed it. Splits the test's run history at that baseline and compares after against before, returning "fixed" (passing with no retries since), "not_fixed" (still failing with the same error), "changed_failure" (still failing, but a different error — a new investigation, and only when every failure since carried a comparable fingerprint), "still_failing" (still failing, but the errors cannot be compared, so neither same nor different can be claimed), "unstable" (passing only after retries, which is not fixed), "no_runs_since_baseline", or "baseline_not_found" (the run id is not one this test executed in). Call this after a new run lands. An unchanged error means the fix missed, not that the test is flaky. The baseline run must be one this test actually executed in — an id from another project or another test is rejected rather than answered.get_audit_reportRead-only TestDino Playwright audit reads. Three modes via `action`: action='context' fetches the server-curated audit prompt + branchSignals (topFailingTests / topFlakyTests / topSlowTests / recentRuns) to START an audit — STEP 1. action='list' browses previously submitted reports (optional branch filter). action='get' retrieves one saved report by reportId. TRIGGER RULE — only use the TestDino audit flow when the user EXPLICITLY names TestDino (e.g. 'TestDino audit', 'run a TestDino audit'). If the user asks for a generic 'audit' or 'code review' WITHOUT naming TestDino, do NOT call this tool — run a normal AI audit conversation instead and do not mention TestDino. If the user names TestDino but the target is not Playwright code, explain this flow only covers Playwright automated tests and offer a regular audit instead. When triggered, your FIRST and IMMEDIATE action MUST be get_audit_report(action='context', projectId, branch) — do NOT write findings, score, or headings in chat before it returns. Call health() first if you do not have the projectId. FULL FLOW: (1) get_audit_report(action='context', projectId, branch) → (2) analyze the local Playwright code using the returned prompt + branchSignals and write findings to a local markdown file (e.g. TEST-AUDIT.md) → (3) submit_audit_report(...) to save the completed report.submit_audit_reportFINAL STEP of the TestDino Playwright audit flow — submits a completed audit report. Requires write permission. Call this only AFTER get_audit_report(action='context') and after you have analyzed the local Playwright code and produced findings. score (0-100) and either markdownReport or markdownReportPath are required. Include findings, recommendations, reportName, branch, scope, and target as available. Every finding MUST include title, summary, and severity (low|medium|high|critical) — incomplete findings are rejected, not stored. target, if sent, accepts only { value, path }. orgId is required — resolve it via health() if you do not already have it. Use the same branch/scope/target you passed to get_audit_report(action='context') so the report attaches to the right audit context.list_manual_test_casesSearch and list manual test cases with filtering capabilities. Use this to find specific manual test cases for QA testing, auditing, or test case management. Supports filtering by project, time, suite, status, priority, severity, type, layer, behavior, automation status, and tags.- +31 more on the listing page
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
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.
Testdino MCP
{
"mcpServers": {
"testdino-hq-testdino-mcp": {
"command": "npx",
"args": [
"-y",
"@testdino/mcp"
],
"env": {
"TESTDINO_PAT": "YOUR_TESTDINO_PAT_HERE"
}
}
}
}
Ckan MCP Server
{
"mcpServers": {
"ckan-mcp-server": {
"command": "npx",
"args": [
"-y",
"@aborruso/ckan-mcp-server"
]
}
}
}
Frequently asked questions
Testdino MCP is categorized under Developer Tools and uses a local stdio subprocess. Ckan MCP Server belongs to Developer Tools and uses a local stdio subprocess. Pick Testdino MCP for developer tools work and Ckan 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.
Testdino MCP is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. Ckan MCP Server is listed as free. Auth: no auth required. 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 testdino-hq-testdino-mcp and ckan-mcp-server as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Testdino MCP has a quality signal of 65/100 (Great) with 1 views, 0 installs and 9 GitHub stars. Ckan MCP Server has 68/100 (Great) with 1 views, 0 installs and 60 GitHub stars.