MCP server

Expose Pipefort’s scanner to AI coding assistants over the Model Context Protocol.

pipefort mcp runs Pipefort as a Model Context Protocol server over stdio, so an AI coding assistant can scan CI workflows as it writes them — catching an injection sink or an unpinned action before the code is ever committed. It wraps the same engine as the CLI and web app.

Register it

Point your assistant at the pipefort mcp command. For Claude Code:

claude mcp add pipefort -- pipefort mcp

For other clients, add a command-based (stdio) MCP server entry, e.g.:

{
  "mcpServers": {
    "pipefort": {
      "command": "pipefort",
      "args": ["mcp"]
    }
  }
}

Tools

Tool	Arguments	Returns
scan_workflow	content (required), filename, ruleset, persona, min_confidence	Findings for a single in-memory workflow file. Set filename to .gitlab-ci.yml to scan GitLab CI; defaults to GitHub Actions.
scan_directory	path (required), ruleset, persona, min_confidence	Findings for a local directory’s .github/workflows/* and .gitlab-ci.yml, plus detected toxic combinations.
explain_rule	rule_id (required)	The catalog entry (title, severity, confidence, description, docs URL) for a rule.

All three are read-only and offline — no token or network required. ruleset, persona, and min_confidence mirror the CLI flags: omit them for the permissive defaults (all / regular / keep everything).

Example

An assistant editing a workflow can call scan_workflow with the buffer contents and surface findings inline:

{
  "name": "scan_workflow",
  "arguments": {
    "content": "on: pull_request_target\njobs: ...",
    "min_confidence": "MEDIUM"
  }
}

The response is the same finding shape as -o json: each finding carries its rule_id, severity, confidence, file, line, and recommendation.