Seldonframe vs Codescene MCP Server
A side-by-side look at the Seldonframe 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 Seldonframe 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 Seldonframe when
- You need dedicated capabilities in the Developer Tools domain.
- You prefer a local stdio subprocess transport.
- You want tools like
create_full_workspace, create_workspace_from_google_paste, create_workspace_from_url.
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 | 65/100 · Great | 65/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 63 | 72 |
| Directory activity | 1 views 0 installs 0 upvotes | 3 views 0 installs 0 upvotes |
| Tools | 160 | 28 |
| Full listing | View Seldonframe | View Codescene MCP Server |
Tools & capabilities
Seldonframe tools 160
create_full_workspaceAtomic workspace creation from pre-extracted business facts. Equivalent to create_workspace_v2 but single-call (no block-by-block iteration). Used as the follow-up after `create_workspace_from_url` for cases where the operator wants the workspace produced in one shot rather than block-iterated. Example: create_full_workspace({ business_name: 'Summit Air Comfort', city: 'Phoenix', state: 'AZ', phone: '(480) 555-2100', services: ['AC repair', 'heating installation', 'duct cleaning'], business_description: 'Residential and commercial HVAC in Phoenix', review_count: 950, review_rating: 4.7, trust_signals: ['licensed', 'bonded', 'insured'], emergency_service: true, same_day: true, service_area: ['Scottsdale', 'Tempe', 'Mesa'] }). MANDATORY FOLLOW-UP: same as create_workspace_v2 — after this returns `status: 'ready'`, ask 'What email should I use for your account?' and call finalize_workspace({ workspace_id, email }).create_workspace_from_google_pastePREFERRED when the operator pastes a Google Maps business listing. Same atomic pipeline as create_full_workspace; this tool's docs guide the paste-to-fields extraction. Claude Code parses the paste BEFORE calling this tool — never pass the raw paste text. EXTRACTION RULES (apply in order): 1) business_name → the bold business title at the top of the listing. 2) phone → the digits next to the phone icon. 3) address → the line next to the location pin. Parse city + state from this address into separate fields (city/state). 4) services → derive from BOTH the categories chip row (e.g. 'Plumber · Emergency plumbing service') AND any explicit 'Services' section ('Drain cleaning', 'Water heater repair'). Dedupe; keep 5-12 distinct strings. 5) business_description → synthesize 1-2 sentences from the categories + 'About' / 'From the business' section. Include industry words verbatim (the personality classifier reads this). 6) review_rating + review_count → the '4.7 ★ (950)' element. 7) trust_signals → 'Licensed', 'Bonded', 'Insured', 'Family-owned' if mentioned. 8) emergency_service / same_day → set true if 'open 24 hours', '24/7', 'same-day service' appears. 9) service_area → cities mentioned in 'Service area' section. 10) weekly_hours → parse the hours block ('Monday: 9 AM-5 PM, Tuesday: closed, ...') into the canonical shape: {monday:{enabled:true,start:'09:00',end:'17:00'},tuesday:{enabled:false,start:'09:00',end:'17:00'},...}. Keys MUST be FULL DAY NAMES (sunday/monday/.../saturday); times MUST be HH:MM 24-hour. 'Closed' → enabled:false (start/end are placeholders). 'Open 24 hours' → start:'00:00', end:'23:59'. These hours are written DIRECTLY to the booking template's availability — wrong shape = booking page falls back to Mon-Fri 9-5 default. 11) google_place_url → the Maps URL the operator pasted, if visible. Optional, stored on soul.business.maps_url for audit. MANDATORY FOLLOW-UP: same as create_full_workspace — after this returns `status: 'ready'`, ask 'What email should I use for your account?' and call finalize_workspace({ workspace_id, email }).create_workspace_from_urlEntry point for URL-based workspace creation. Returns instructions Claude follows: WebFetch the URL, optionally WebFetch up to 2 priority sub-pages (e.g. /about, /services, /contact, /pricing), extract structured business facts, ask the operator for any required field that can't be determined, then call `create_full_workspace` with the result — ONE atomic call that builds the workspace + the production multi-page website (vertical-aware landing + per-service detail pages, the same engine as the SeldonFrame dashboard) + booking page + intake form + CRM + draft chatbot. THIS TOOL DOES NOT CREATE A WORKSPACE — it returns the playbook. The workspace is created by the follow-up `create_full_workspace` call. Do NOT use the block-iterated create_workspace_v2 flow for URL builds. When operator provides ANY of: 'http://', 'https://', a domain (.com/.io/.net/.co/.app/.dev/.us etc), or 'create workspace for <URL>' — call this tool. Do NOT manually WebFetch first; the instructions returned by this tool tell you exactly what to fetch and in what order. MANDATORY FOLLOW-UP: After create_full_workspace returns, ask the operator 'What email should I use for your account?' and call finalize_workspace({ workspace_id, email }).generate_landing_pageGenerate a SeldonFrame-hosted landing page for an EXISTING workspace. USE-WHEN: operator explicitly asks for a landing page after the workspace exists, OR the client has no website of their own and the agency wants SeldonFrame to host the public-facing site. If the client already has a website (the common agency case), the chatbot embed snippet returned by create_workspace_from_url is the canonical deliverable; you do NOT need a generated landing page. Latency: ~30-60s. Returns the public landing URL. Operator can later customize per-block via update_landing_section / persist_block.list_workspacesList all workspaces known to this device (plus any Pro workspaces if SELDONFRAME_API_KEY is set).switch_workspaceSet the active workspace. Subsequent tool calls act on it by default.clone_workspaceClone an existing workspace as a template. Example: clone_workspace({ source_workspace_id: 'wsp_x', name: 'Copy' })link_workspace_ownerClaim an anonymously-created workspace under your real account. After linking, the admin URLs (dashboard, contacts, deals) become usable once you sign in at app.seldonframe.com. Requires SELDONFRAME_API_KEY to be set in the MCP environment. The workspace bearer token continues to work — no rotation needed. Example: link_workspace_owner({}) to claim the active workspace.send_welcome_emailEmail the active workspace's four key URLs (landing, booking, intake, admin dashboard) to a user. Use this AFTER create_workspace, only when the user has explicitly given their email — never auto-send. The admin URL is bearer-token-scoped and expires in 7 days. If the workspace has an AI chatbot (create_full_workspace's response includes chatbot_embed_snippet + chatbot_agent_id), pass chatbot_url + chatbot_embed_snippet + chatbot_status so the welcome email also shows the chatbot card with its embed snippet — operators otherwise never learn the workspace shipped with a chatbot. All three are optional; omit them to send the classic 4-URL email. Example: send_welcome_email({ email: 'alice@example.com', name: 'Alice', chatbot_url: 'https://acme.app.seldonframe.com/chat', chatbot_embed_snippet: '<script src="..." async></script>', chatbot_status: 'test' }).collect_operator_emailMANDATORY post-workspace step. Send the operator's welcome email + record them as a lead in SeldonFrame's CRM. EVERY workspace creation flow MUST end with this call — it is the only thing that triggers the welcome email (with the live URLs), creates their account so the admin login keeps working past the 7-day token, captures them in our pipeline so we can follow up, and lets Stripe pre-fill their email on upgrade. Skipping it leaves the operator with a one-shot URL and no way to recover access. Flow: after create_workspace returns, ask the user verbatim 'What email should I use for your account? This is where you'll get your login link and any notifications.' Then call this tool with whatever email they give you. If you'd rather use the wrapper, call `finalize_workspace({ email })` instead — same effect plus a formatted summary at the end. Example: collect_operator_email({ email: 'max@precisionplumbing.com', name: 'Max' })finalize_workspaceONE-CALL CLOSING WRAPPER for the workspace creation flow. Bundles email collection (welcome email + lead capture via collect_operator_email) AND produces the final operator-facing summary (live URLs, what's configured, admin link). Call this as the LAST step of every workspace creation. After create_workspace returns, ask the user 'What email should I use for your account? This is where you'll get your login link and any notifications.' Then call this tool with the email they give you. Returns a `summary` string Claude Code should paraphrase verbatim to the operator. Use this instead of calling collect_operator_email directly when you want a single tool call to close the loop. Skipping this is the same as skipping email collection — leaves the operator with a one-shot URL and no recovery path. Example: finalize_workspace({ email: 'max@precisionplumbing.com', name: 'Max' }). The summary is agency-voice: addresses the operator AS an agency delivering for their SMB client, not as the workspace owner. When relaying to the operator, preserve the 'your client' framing throughout — don't rewrite to 'your workspace'.revoke_bearerRevoke workspace bearer tokens. Useful if a device token has leaked or if a builder wants to rotate. Modes (pick exactly one): `{}` revokes ALL tokens except the current device's (safe default — other devices kicked off, this device keeps working); `{ token_id }` revokes a specific token by its UUID; `{ all: true }` revokes every token including the current one — requires SELDONFRAME_API_KEY because it locks this device out. After revoking the current token the MCP clears the local entry from ~/.seldonframe/device.json.- +148 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.
Seldonframe
{
"mcpServers": {
"mcp-324": {
"command": "npx",
"args": [
"-y",
"@seldonframe/mcp"
]
}
}
}
Codescene MCP Server
{
"mcpServers": {
"codescene-mcp-server": {
"command": "npx",
"args": [
"-y",
"@codescene/codehealth-mcp"
]
}
}
}
Frequently asked questions
Seldonframe 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 Seldonframe 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.
Seldonframe has no declared pricing — check the project's own site. 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 mcp-324 and codescene-mcp-server as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Seldonframe has a quality signal of 65/100 (Great) with 1 views, 0 installs and 63 GitHub stars. Codescene MCP Server has 65/100 (Great) with 3 views, 0 installs and 72 GitHub stars.