dotrepo

Look up a repository's purpose, build and test commands, docs, and owners.

dotrepo is an open repository metadata protocol with a reference toolchain and public index. It gives agents and tools those facts as JSON, through MCP, or from a local .repo file. Each record includes source and trust context so you can decide whether to use an answer or inspect upstream.

Try it: orient yourself in ripgrep

Fetch the indexed profile without installing anything or cloning the repository:

curl -sS https://dotrepo.org/v0/repos/github.com/BurntSushi/ripgrep/profile.json

The response groups purpose, execution, documentation, and ownership. Check record.generatedAt, record.freshnessStatus, conflicts, and the fields your task needs. freshness.generatedAt dates the export, not the source facts. A missing, old, or conflicting answer needs an upstream check. Returned commands are data to review, not permission to execute them.

Connect your agent

Install the stable MCP server with a Rust toolchain, or use the stable release bundle:

cargo install dotrepo-mcp --version 1.0.3 --locked

For clients that use an mcpServers configuration:

{
  "mcpServers": {
    "dotrepo": { "command": "dotrepo-mcp", "args": [] }
  }
}

Ask the client to call dotrepo.lookup with these arguments:

{
  "repositoryUrl": "https://github.com/BurntSushi/ripgrep",
  "path": "repo.test"
}

See installation for the CLI, LSP, and VS Code extension, and consumer integration for fallback rules and a runnable client.

Version matters: the stable release is v1.0.3; this branch is unreleased 2.0.0-alpha.0. Stable includes the bounded command-extraction fixes, the promotion no-write guard, and response-size caps. The newer field-evidence schema, execution contexts, and additional MCP target checks remain on main. Use the version comparison and stable documentation.

What you can use it for

• Repository orientation: get purpose, docs, owners, and reported commands before deciding what source files to inspect
• Agent integrations: make a first lookup, retain trust and age, then fall back to upstream when the answer does not meet your task's needs
• Maintainer metadata: keep a native .repo file and supported documentation blocks consistent with validation and generated-surface checks
• Repository discovery: search, compare factual profiles, and traverse repository relationships through the public API

Indexed overlays are generated from public source material, so maintainers do not need to adopt dotrepo for their repository to appear. A native .repo provides maintainer control. Routine generated records are machine-checked; verified does not mean human-reviewed or correct in every field.

Add a record to your repository

Install the stable CLI from the release bundle or with cargo install dotrepo-cli --version 1.0.3 --locked, then:

# Start from existing README.md, CODEOWNERS, and SECURITY.md:
dotrepo --root <repo> import
# Review the generated .repo, then:
dotrepo --root <repo> validate
dotrepo --root <repo> query repo.build --raw
dotrepo --root <repo> trust
dotrepo --root <repo> generate --check

Use init instead of import to start from a blank scaffold. The stable maintainer guide walks through adoption; sync boundaries explain which files and regions dotrepo can manage.

Limits and evidence

• Metadata supports orientation. Architecture research, suitability decisions, debugging, and code changes still require source inspection
• Coverage, correctness, completeness, and freshness are separate. Records can be incomplete, stale, or wrong even when marked verified; retained field-level evidence is available only where the producing version and crawl saved it. See the trust model
• The measurement page reports field presence and modeled requests. Those are not accuracy or measured end-to-end agent savings
• The head-to-head benchmark keeps wins and losses against a GitHub API + README baseline. Fixing its examples is regression evidence, not proof of generalization
• Sustained independent consumer adoption remains an open success criterion. In-repository clients and AI interviews do not establish external demand

Read next

• Documentation map and release compatibility
• Toolchain and protocol reference, including MCP tools, validation scope, and version boundaries
• Hosted API examples, public architecture, and own-project study and later pilot
• Trust model and authority rules
• Roadmap, contributing, and index operations

For implementation, start with the roadmap packets and team execution guide. Repository guidance owns contracts; generated reports and dated archives own outcome evidence.

Repository Python tooling uses uv: run uv venv, uv sync --dev --locked, then invoke scripts and tests through uv run.