Conducted MCP

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.

Category
Visit Server

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 (kickoff prompt + kickoff_questions / kickoff_plan tools) — 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


License

MIT © 2026 Jonathan Mostov

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured