DevMatch
Server Details
MCP server for Cursor/Claude Code: paste a JD or README, get ranked engineers by verified work.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.7/5 across 3 of 3 tools scored.
Each tool targets a distinct operation: finding candidates by job description, finding similar projects to a repo, and fetching individual profiles. No overlap in purpose.
All tools follow a consistent verb_noun pattern using snake_case: find_candidates, find_similar_projects, get_profile. Predictable and clear.
With 3 tools, the set is slightly small but still covers the core functionalities of candidate search, project exploration, and profile lookup. It's reasonable for a focused server.
The tool surface covers the main needs: searching candidates (with full profile data embedded), finding similar projects, and fetching individual profiles. Minor gaps like filtering or updating do not hinder the core matching workflow.
Available Tools
3 toolsfind_candidatesARead-onlyIdempotentInspect
Search the DevMatch index for engineers matching a job description. Pass JD text — formal description, informal request, role brief, paste of a README, or anything in between. The longer + more specific, the better the match. Returns ranked candidates with FULL profile data inline per result: handle, name, bio, location, followers, top_repos, top_topics, matched_projects (with contribution counts), contact info (email + social URLs when available), and candidate_score. You do NOT need to call get_profile for candidates returned here — their profiles are already embedded in the response. Only call get_profile when the user asks about a handle that was NOT in the find_candidates results.
Public github.com repo URLs are also accepted as input (server fetches README + topics + language and uses it as the JD), but ONLY for PUBLIC repos. For private repos, paste the README content directly as the JD string.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | Job description text (preferred), OR a PUBLIC github.com repo URL. For private repos, paste the README content as text instead of the URL. The richer the input, the better the ranking. |
Output Schema
| Name | Required | Description |
|---|---|---|
| query_ms | No | End-to-end query time in milliseconds |
| candidates | Yes | Ranked engineer candidates. Highest candidate_score first. |
| total_count | Yes | Count of candidates returned (≤ requested limit) |
| cache_source | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, idempotentHint, destructiveHint) indicate safe, non-destructive operation. The description adds substantial context: it describes the response structure (ranked candidates with full profile data inline per result), states you don't need to call get_profile, and clarifies accepted input types and their limits. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose. Every sentence contributes essential information: input types, best practices, output details, and differentiation from sibling tools. Despite its length, it is efficient and avoids redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 1 parameter and rich output (implied by 'full profile data inline', matched_projects, contact info), the description fully explains input expectations, output content, and behavioral nuances (repo URL handling). It covers all aspects an agent needs to use the tool correctly without additional lookups.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'input' has 100% schema description coverage, but the description significantly expands its meaning: it explains the flexibility of input (formal JD, informal request, README paste, etc.), the advantage of length and specificity, and the special case of public repo URLs vs. private repos. This adds crucial semantic context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search the DevMatch index for engineers matching a job description.' It specifies the action (search), resource (DevMatch index), and expected outcome (engineers matching JD). It also differentiates from sibling tools by noting that returned candidates include full profiles, so get_profile is unnecessary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance (pass JD text or public repo URL) and when-not-to-use (do not call get_profile for candidates returned here). It also explains alternatives for different input types (private repos: paste README instead of URL). This clearly distinguishes from siblings like get_profile.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_similar_projectsARead-onlyIdempotentInspect
Find open-source projects similar to a given GitHub repo, ranked by semantic similarity to its description/topics/README. Each result includes the project's top contributors so the caller can pivot from a project to its maintainers in one step. Use for landscape mapping ("what else is like X?"), competitive intel, or to expand a candidate search past a single anchor project.
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | Seed repo in `owner/name` form (e.g. 'karpathy/llm.c'). A full github.com URL is also accepted; the server strips the prefix. | |
| limit | No | Number of similar projects to return. Defaults to 10, max 25. |
Output Schema
| Name | Required | Description |
|---|---|---|
| projects | Yes | Similar projects, ranked by vector similarity to the seed repo. |
| seed_repo | No | The owner/name that was searched against |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value beyond these by explaining the ranking method (semantic similarity) and the inclusion of top contributors in results. It also clarifies that the tool operates on GitHub repositories and outputs an ordered list, which is not covered by annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each serving a distinct purpose: first sentence states core functionality, second highlights key output feature (contributors), third lists use cases. It is front-loaded with the main action, no redundant words, and every sentence adds value. It is highly efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (takes a repo and limit, returns similar projects with contributors) and the presence of an output schema, the description covers all essential aspects: input, output, ranking method, and inclusion of contributors. It does not discuss error handling, but those are generally not expected. The use cases provide additional context. Slightly incomplete regarding potential edge cases (e.g., no results), but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add parameter-specific details beyond what the schema provides. The description mentions ranking by similarity but does not explain how parameters like 'limit' affect the score or behavior. The schema already adequately documents both parameters, so the description does not require additional semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds open-source projects similar to a given GitHub repo using semantic similarity. It specifies the verb 'Find', the resource 'similar projects', and the method 'semantic similarity to its description/topics/README'. The use cases (landscape mapping, competitive intel, candidate expansion) further clarify purpose. It is well-differentiated from siblings like find_candidates (which presumably finds candidates generally) and get_profile (which retrieves profile details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists three concrete use cases: landscape mapping, competitive intel, and candidate search expansion. This provides clear context for when to use the tool. However, it does not explicitly state when not to use it or compare it to alternatives like find_candidates, leaving the agent to infer boundaries. The guidance is clear but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_profileARead-onlyIdempotentInspect
Fetch one contributor's profile card when the user mentions a specific GitHub handle that was NOT already returned by find_candidates. Use cases: (a) user types 'tell me about @karpathy'; (b) user references a handle they found elsewhere; (c) user wants to verify someone before outreach. Do NOT call this immediately after find_candidates for handles in those results — find_candidates already returns full profile data inline per candidate (bio, location, contact, top_repos, top_topics).
IMPORTANT — interpreting recent_activities: this field reflects indexed GitHub activity in the current ingestion window (2025–2026), up to ~20 events per recent project. It is NOT a complete career history. Older or empty activity does not mean the person is inactive; they may be outside the index window or not yet enriched. Do not infer tenure or 'last active' from activity older than 2025.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | The GitHub handle to look up. Plain login name, no '@' prefix (e.g. 'karpathy', not '@karpathy'). |
Output Schema
| Name | Required | Description |
|---|---|---|
| bio | No | |
| name | No | |
| No | ||
| company | No | |
| html_url | No | Profile URL on GitHub |
| location | No | |
| followers | No | |
| avatar_url | No | |
| login_name | Yes | GitHub handle |
| display_name | No | |
| public_repos | No | |
| top_projects | No | Highest-contribution projects this user worked on |
| profile_readme | No | User's profile README content if present |
| social_accounts | No | Social URLs (twitter, linkedin, etc.) |
| recent_activities | No | Indexed GitHub events from current ingestion window (2025–2026). NOT a full career timeline. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds critical context about 'recent_activities': it reflects only 2025–2026 indexed activity (~20 events per project) and is not a complete career history. It also warns against inferring inactivity from missing or old data, going well beyond the structured annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loading the purpose and use cases, then providing important caveats about data freshness. Every sentence adds value without redundancy. Ideally sized for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and annotations, the description covers all necessary aspects: invocation context, parameter format, data limitations, and behavioral notes. There are no gaps for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear description for the single 'handle' parameter. The description adds practical guidance (plain login name, no '@' prefix), which is useful but not essential given the schema. Minor added value justifies a slight bonus above baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches a contributor's profile card for a specific GitHub handle, with explicit use cases (e.g., user mentions a handle, references from elsewhere, verification). It distinguishes itself from the sibling 'find_candidates' by noting that find_candidates already returns full profile data for handles in its results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use (e.g., handle not in find_candidates results) and when not to (do not call immediately after find_candidates for handles already returned). Lists three specific use cases, giving clear context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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