github-talent-mcp 0.2.0

MCP server for searching, scoring, and ranking GitHub developers for technical recruiting

github-talent-mcp

MCP server that searches, scores, and ranks GitHub developers for technical recruiting.

Demo

https://github.com/user-attachments/assets/b2dbe9e0-26ee-4849-861a-4b5cb268facc

Sourcing candidates for a real Anthropic JD, live in Claude Cowork.

https://github.com/user-attachments/assets/2dfd82b4-3eb5-4f2b-bc0a-2580b95043e4

Profile deep dive

Get the full developer profile and activity score for torvalds on GitHub

Claude calls get_developer_profile("torvalds") and returns:

Field	Value
Activity Score	150 (reputation floor applied)
Location	Portland, OR
Followers	293,321
Stars Received	235,068
Primary Language	C (98.1%)
Commits (90d)	0
PRs (90d)	0
Notable Repos	linux (183K stars), libdc-for-dirk, subsurface-for-dirk, uemacs, pesern-resolve
Profile README	No
Hireable	No

Torvalds has zero recent GitHub activity because kernel development flows through mailing lists, not GitHub PRs. The reputation floor (293K followers) overrides the behavioral score and sets it to 150.

Repo contributor ranking

Get the top contributors to huggingface/transformers and rank them for a founding ML engineer role at an AI startup

Claude calls get_repo_contributors("huggingface/transformers") → rank_candidates on the top 24 contributors:

Rank	Developer	Combined Score	Activity	Relevance	Strengths
1	stas00	83.4	150	72	4,553 stars, contributes to major OSS, MIT-licensed repos
2	cyyever	80.8	120	64	1,217 followers, active contributor, profile README
3	Cyrilvallez	77.2	120	56	Active: 13 commits + 57 PRs in 90 days, strong OSS presence
4	ArthurZucker	74.4	120	48	37 PRs in 90 days, contributes to huggingface/transformers
5	ydshieh	72.0	120	40	Active: 9 commits + 40 PRs in 90 days

Combined score = activity × 0.4 + relevance × 0.6. Relevance is keyword overlap with the job description (ML, AI, startup, engineer, etc.).

Installation

1. Clone and install

git clone https://github.com/carolinacherry/github-talent-mcp.git
cd github-talent-mcp
python3 -m venv .venv && source .venv/bin/activate
pip install -e .

2. Create a GitHub personal access token

Go to github.com/settings/tokens and create a fine-grained or classic token with these scopes:

Scope	Why
read:user	Read user profiles and search users
public_repo	Read public repo data, languages, contributors

Create a .env file in the project root:

GITHUB_TOKEN=ghp_xxxxxxxxxxxx

3. Connect to Claude

Claude Code (CLI)

One command:

claude mcp add github-talent -- /path/to/github-talent-mcp/.venv/bin/python3 -m github_talent_mcp

Then set the token as an environment variable. Either:

• Export it in your shell: export GITHUB_TOKEN=ghp_xxxxxxxxxxxx
• Or keep it in the .env file — the server reads it via python-dotenv on startup

Restart Claude Code to pick up the new server. Verify with /mcp — you should see 8 tools under github-talent.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "github-talent": {
      "command": "/path/to/github-talent-mcp/.venv/bin/python3",
      "args": ["-m", "github_talent_mcp"],
      "cwd": "/path/to/github-talent-mcp",
      "env": {
        "GITHUB_TOKEN": "ghp_xxxxxxxxxxxx"
      }
    }
  }
}

Restart Claude Desktop. The tools will appear in the toolbox icon.

GitHub Copilot (CLI & desktop app)

The GitHub Copilot CLI and the GitHub Copilot app share one MCP config, so a single setup covers both.

One command (Copilot CLI):

copilot mcp add github-talent -e GITHUB_TOKEN=$GITHUB_TOKEN -- uvx github-talent-mcp

Or add it manually to ~/.copilot/mcp-config.json:

{
  "mcpServers": {
    "github-talent": {
      "type": "local",
      "command": "uvx",
      "args": ["github-talent-mcp"],
      "env": {
        "GITHUB_TOKEN": "${GITHUB_TOKEN}"
      },
      "tools": ["*"]
    }
  }
}

Export your token first (export GITHUB_TOKEN=ghp_xxxxxxxxxxxx) — Copilot only inherits PATH, so the ${GITHUB_TOKEN} reference reads it from your shell. If uvx isn't on your PATH, use its absolute path as command.

The Copilot app picks up this same config; it also syncs a repo's .copilot/mcp-config.json automatically and lets you add servers under Settings → MCP. Verify with copilot mcp list (terminal) or /mcp show (in a Copilot session) — you should see 8 tools under github-talent.

Try It

Once installed, paste these prompts to verify everything works:

Basic search:

Find Python developers in Raleigh active in the last 60 days

Profile deep dive:

Get the full developer profile and activity score for torvalds on GitHub

Full workflow:

Find 10 ML engineers in San Francisco active in the last 30 days, then rank them for a senior LLM inference engineer role

Repo contributors:

Get the top contributors to huggingface/transformers and rank them for a founding ML engineer role at an AI startup

JD scoring:

Score these candidates against this job description: [paste JD]. Candidates: tiangolo, karpathy, hwchase17

Compare candidates:

Compare tiangolo and hwchase17 for a Senior Python AI Engineer role

Bulk scoring:

Score these 10 GitHub usernames and give me a ranked table: [paste list]

Outreach:

Generate a casual recruiter message for tiangolo about a Senior Python role at Acme. My name is Daniel.

Tools

Tool	Description
search_developers	Search GitHub users by language, location, activity, followers. For topic-based sourcing, use get_repo_contributors on relevant repos instead.
get_developer_profile	Deep profile enrichment: languages, stars, commits + PRs, OSS contributions, license breakdown, profile README, and activity score with breakdown.
rank_candidates	Rank usernames against a job description. Returns sorted candidates with combined score, strengths, gaps, and reasoning.
score_against_jd	Score candidates against a JD with per-dimension breakdown (tech stack, experience level, OSS signal, leadership). Returns gaps and personalized interview questions.
compare_candidates	Side-by-side comparison of 2-5 candidates. Shows dimension winners and a recommendation. Optionally scored against a JD.
bulk_score	Score up to 100 GitHub usernames in one call. Returns a ranked markdown table or CSV. Supports optional JD matching.
generate_outreach	Generate personalized recruiter messages (short/medium/detailed) that reference the candidate's actual repos and contributions. Requires your company name and sender name. Casual or formal tone.
get_repo_contributors	Top contributors for any repo. Accepts owner/repo or full URL. The fastest way to source for a specific domain.

Scoring

The activity score combines two layers: behavioral signals (what you did recently) and a reputation floor (what you've built over time).

Behavioral Score (0-205)

Signal	Max Points	How
Commits + PRs (last 90 days)	60	Push commits + PR opens (PRs weighted x3). Captures both push-based and PR-based workflows.
Stars on repos	40	Personal repo stars + stars on repos you contribute to. Org repo maintainers get credit.
Profile README	20	Presence of a profile README (github.com/username/username).
Followers	20	Capped at 20.
Repos with descriptions	20	Ratio of repos that have descriptions. Signal of care and polish.
Permissive license repos	15	Has at least one repo with MIT, Apache-2.0, BSD, ISC, or Unlicense.
Major OSS contributions	30	PRs, pushes, or issues on repos you don't own. Capped at 3 repos (10 pts each).

Reputation Floor

The behavioral score alone penalizes developers whose work doesn't produce GitHub events — Torvalds works through mailing lists, senior maintainers merge via org bots, and many engineers work in private repos.

The reputation floor ensures cumulative impact isn't erased by a quiet quarter:

Threshold	Floor
10K+ followers or 50K+ stars	150
1K+ followers or 5K+ stars	120
500+ followers or 1K+ stars	100
100+ followers or 200+ stars	80

The final score is max(behavioral_score, reputation_floor). If the floor is applied, the breakdown includes a reputation_floor field so you know.

Score Tiers

• 150+ — exceptional (top OSS maintainers, well-known engineers)
• 120-149 — strong signal, worth reaching out
• 80-119 — solid developer with meaningful public work
• 40-79 — active but limited public signal
• <40 — low signal (likely private work or junior)

Ranking

rank_candidates combines the activity score with a relevance score (0-100) based on keyword overlap between the job description and the candidate's profile (bio, languages, repo topics, README). The combined score weights relevance at 60% and activity at 40% — a high-activity developer with no overlap to the job shouldn't outrank a relevant one.

Rate Limits

GitHub REST API: 5,000 requests/hour with token. A typical workflow (search + enrich 5 candidates + rank) uses ~60-100 API calls. Profile results are cached within a session to avoid redundant calls during ranking.

License

MIT