github-talent-mcp

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

Demo

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. Install

pip install github-talent-mcp

Or install from source:

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 4 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.

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

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. | | 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.

Security

For reproducible installs with pinned versions, use the lockfile:

pip install -r requirements-lock.txt
pip install github-talent-mcp

This pins every transitive dependency to the exact version tested against. If you're security-conscious about supply chain attacks, verify package hashes with pip-audit or install with --require-hashes.

License

MIT

MCP Servers