Conducted MCP
An MCP server that helps AI agents plan and track software projects using the Conducted Development methodology, providing artifact validation, kickoff guidance, and project rituals.
README
Conducted MCP
An MCP server that helps an AI agent plan and track a software project the way a disciplined team would — and it was built using the very methodology it ships.
Conducted MCP exposes Conducted Development — a lightweight, intent-driven methodology — to any MCP-capable agent (Claude Desktop, Cursor, and others). It is a stateless advisor + validator: it holds no project data and touches no files or git. The agent does all the I/O; the server supplies judgment — validate this artifact, is a standup due, what's the procedure for this phase, does this decision belong in the log.
The differentiator: this repository's own
work/folder — goal briefs, intent docs, a decision log, and cycle standups — was produced under the methodology the tool implements. It is the proof of process, not a sample.
What it does
A connecting agent gets, on demand:
- A guided kickoff (
kickoffprompt +kickoff_questions/kickoff_plantools) — a branching Q&A that bootstraps a project's planning structure for greenfield or existing codebases. For existing code the agent inspects the repo and the server pre-fills answers so the human confirms rather than authors from scratch. - Strict artifact validation (
validate_artifact) — submit a goal brief / intent doc / session log / standup, get back{ valid, missing, warnings }. - Phase procedures (
next_procedure) — the ordered steps, what to read first, and the escalation points for wherever the agent is in the loop. - Mechanical rule checks (
standup_due,evaluate_gate,decision_log_guidance) — the rituals a solo practitioner most often lets slide, as stateless judgments over supplied facts.
The methodology's guides, templates, and conventions are served as read-only resources (conducted://guide/*, conducted://template/*, conducted://conventions) so an agent can learn the rules in-band.
Why it's built this way (Model C)
The server cannot enforce — an agent always has direct file access. So instead of pretending to be a gatekeeper, it is an advisor: pure functions returning judgments and procedures, no side effects, nothing to host with no data and no auth-to-data. That makes it portable, trivially testable, and cheap to run locally or remotely. The reasoning is written up in docs/DESIGN_SKETCH.md and the resolved trade-offs in DECISIONS.md.
Quick start
Published on npm as conducted-mcp — runs with zero install via npx.
Add the server to your MCP client. Claude Desktop (claude_desktop_config.json) or Cursor (.cursor/mcp.json):
{
"mcpServers": {
"conducted": {
"command": "npx",
"args": ["-y", "conducted-mcp"]
}
}
}
Then ask your agent to "run the Conducted kickoff for this project," or call any tool directly.
Or connect to the hosted endpoint (no install)
A stateless Streamable HTTP endpoint runs live on Cloudflare Workers — connect by URL, nothing to install:
{
"mcpServers": {
"conducted": {
"url": "https://conducted-mcp.jonathanmostov.workers.dev/mcp"
}
}
}
Because the server is stateless and holds no data (Model C), the endpoint is safe to run unauthenticated, guarded by rate limiting.
Demo
See docs/DEMO.md for a real transcript of the kickoff flow — the front-door prompt, the branched interview, and the phase procedures — captured verbatim from the running server. <!-- a client-side screen recording will be added here -->
Development
npm install
npm run build # bundles the methodology text, then strict tsc
npm test # vitest
npm run lint # eslint + prettier
npm start # run the stdio server
The server is TypeScript on the official @modelcontextprotocol/sdk, ESM, strict mode. See CONTRIBUTING.md for the layout and conventions.
The methodology, in the repo
work/goal-briefs/— the goal briefs that drove this buildwork/intent-docs/— one per ticket, the per-session contractswork/standups/— cycle-gate standupswork/decision-log.md— the append-only record of decisionsAGENT_CONVENTIONS.md— how every session runs, model- and tool-agnostic
License
MIT © 2026 Jonathan Mostov
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