Tently MCP
OfficialProvides AI agents with access to Tently's decision store for GitHub pull requests, enabling search of team decisions and impact zone queries scoped to the current GitHub repository.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Tently MCPbefore I refactor src/auth/session.ts, check team decisions and who calls refreshToken"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Tently MCP: AI pull request review, inside your coding agent
Tently is an AI code reviewer for GitHub pull requests. It catches the two things diff-only reviewers miss: regressions in code that depends on the change, and changes that break design decisions your team made on purpose. It learns those decisions from your merged pull requests, review threads and docs, and checks every pull request against them.
This repo is Tently's MCP server: the same decisions, inside Claude Code, Cursor or Codex while the agent writes code, before a pull request exists.
How the pieces fit
Tently is one decision store with two gates:
Gate | When | What it does |
Pull request review (GitHub App) | Every PR | Posts a check run and inline comments for regressions and decision drift, with the evidence attached |
This MCP server | While the agent writes | Lets the agent look up the decisions that apply and the blast radius of a change |
The MCP server needs a Tently workspace. Request early access at tently.dev.
Related MCP server: coderadius
Set up
Create an API key on the Connect page at app.tently.dev, then run this from your repo root:
npx @tently/mcp init --agent claude --api-key <your key>Or pass the key through the environment:
TENTLY_API_KEY=<your key> npx @tently/mcp initinit adds the tently server to .mcp.json (Claude Code) or .cursor/mcp.json (Cursor), and
installs a small skill that tells the agent when to use it. It backs up any file before editing
it, keeps your other MCP servers, and prints every change. Restart your agent afterwards.
--agent takes claude, cursor, both or auto (the default, which detects what's in the
repo).
Manual config
{
"mcpServers": {
"tently": {
"command": "npx",
"args": ["-y", "@tently/mcp", "mcp"],
"env": { "TENTLY_API_KEY": "<your key>" }
}
}
}What the agent gets
search_decisions: the decisions that apply to the code it's about to change, from your Tently workspace. Each one says whether breaking it is blocking or advisory. The search is scoped to the repo you're in (read from the checkout's git remotes), so decisions from your workspace's other repos don't crowd out this one's.query_impact_zone: the blast radius of a symbol (who calls it, what it depends on), computed locally on your checkout with CodeGraph. Your source code never leaves your machine. The index lives in.codegraph/, whichinitadds to.gitignore.
Impact results are evidence, not proof: callers reached through interfaces, dynamic dispatch or re-exports can be missed, and the tool says so in its output.
Configuration
Variable | Meaning |
| Workspace API key (required for |
| API origin, default |
| Directory |
| GitHub repo to scope |
Privacy
search_decisions sends your query text, the file paths you pass and the owner/name of the checkout's origin and upstream remotes to
the Tently API. Nothing
else leaves your machine: query_impact_zone runs entirely locally. See
tently.dev for how Tently handles data.
Development
npm install
npm test
npm run build
node dist/cli.js mcp # start the server on stdioRequires Node.js 20 or later.
Contributing
Issues and pull requests are welcome. For anything beyond a small fix, please open an issue first so we can agree on the approach.
License
This server cannot be deployed
Maintenance
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