Orchestrate MCP
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OrchestrateMCP is the planning brain for agentic workflows.
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- orchestratemcp
- Categories
- Developer Tools, AI, Automation, Project Management
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Setup
Install Orchestrate MCP in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/orchestratemcp/OrchestrateKIT-MCP
Follow the installation instructions in the repository README, then restart your MCP client.
OrchestrateMCP is the planning brain for agentic workflows.
An evidence-backedworkflow-design advisorfor AI agents. Connect it to ChatGPT, Claude (web), Cursor, or Claude Desktop and it plans safer, more grounded AI workflows from a documented component graph and published playbooks. Read-only, stateless, holds no secrets.
Status:hostedhealth_checkreports 64 components, 151 connections, 4 workers, 1 reference stack, 12 published routes, and 12 published playbooks; available over stdio and as a free hosted endpoint (https://mcp.orchestratemcp.dev/mcp). See thepublic claim ledgerfor definitions, evidence, and held claims.
OrchestrateMCP exposes a structured registry of:
components → the building blocks of AI workflows edges → documented relations between components (requires, safer_with, conflicts_with, …) stacks → opinionated technology choices for different deployment contexts routes → published or candidate paths through the component graph playbooks → published patterns with implementation guidance
When a user describes a workflow goal, the MCP can:
- Match the goal to required capabilities and components.
- Traverse documented component relationships and surface their evidence state.
- Reuse sections of known published playbooks.
- Compose a candidate route when no exact playbook exists.
- Score route confidence (coverage, tested edges, stack fit, safety, simplicity).
- Return the route as structured implementation context for Cursor or Claude.
- MCP server runs on stdio (Cursor, Claude Desktop) and over Streamable HTTP / a Cloudflare Worker (ChatGPT, claude.ai) — 18 registered tools.
- health_checkreturns{ name, version, registry: { component_count, edge_count, stack_count, route_count, playbook_count, worker_count, untested_edge_pct } }.
- Hosted registry: 64 components, 151 connections, 1 reference stack, 12 published routes, 12 published playbooks, 4 workers.
- Coverage accounting reports unmatched demand and unsupported supply instead of silently pretending the graph covers everything.
- export_build_briefcan emit a Plan Passport: a deterministic build/test contract for agents and future LAB ingestion, not a runtime verifier.
- Corpus regression tests and release-trust floors ratchet the registry forward in CI.
- pnpm verify(typecheck + lint + tests) passes from a clean clone and install.
OrchestrateMCP is stateless, read-only, holds no secrets, and makes no LLM calls inside its tools. Plans are composed from registry YAML, provenance tags mark computed fields, coverage accounting calls out unsupported pieces, and corpus contracts plus release-trust checks run in CI to catch drift. Registry evidence is not a promise that a proposed workflow is production-ready; see theclaim ledger.
Project policies:Contributing·Security·Changelog
cd orchestratekit-mcp pnpm install pnpm verify # typecheck + tests — must pass before anything else pnpm dev # starts the MCP server on stdio
The server reads fromstdinand writes JSON-RPC tostdout. All log output goes tostderr.
Copyexamples/cursor-mcp.jsoncontent into your Cursor workspace MCP config at.cursor/mcp.json. Replace thecwdvalue with the absolute path to this directory.
{ "mcpServers": { "orchestratekit": { "command": "npx", "args": ["tsx", "src/server.ts"], "cwd": "/absolute/path/to/orchestratekit-mcp" } } }
macOS:~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:%APPDATA%\Claude\claude_desktop_config.json
{ "mcpServers": { "orchestratekit": { "command": "npx", "args": ["tsx", "src/server.ts"], "cwd": "/absolute/path/to/orchestratekit-mcp" } } }
Connect from ChatGPT or claude.ai (hosted)
No install, no terminal — point your AI client at the free hosted endpoint:
Full walkthrough (ChatGPT Developer-Mode connector + claude.ai):docs/CHATGPT_USAGE.md.
After connecting, paste this wrapper plus one starter goal. The default response should be a short product card: title, route, steps, connections, safety note, build controls, and four continuation choices.
Use the orchestratekit MCP tools. Goal: [paste one starter goal here] Call plan_workflow with this goal and render the returned summary_markdown verbatim, including the A) B) C) D) continuation menu.
Build an agent that checks 5 competitor pages every morning, detects price changes, and sends me a Slack summary. I want to approve before anything external is changed.
Build an agent that reads new leads from Gmail, drafts a reply, updates the CRM, and alerts sales in Slack after approval.
When a pull request opens on GitHub, review the diff for bugs and risky changes, notify reviewers with a summary, and never edit or commit code.
When a PDF invoice arrives in the shared AP Gmail inbox, extract totals and line items, match against purchase orders, notify AP in Slack for discrepancies, and hold every invoice for human approval before accounting.
Use a content brief to generate social copy variants and a design brief, send it to a reviewer for approval, then publish externally only after approval.
More first-run starters and expected output shapes:docs/FIRST_RUN_STARTERS.md.
Connecting your workflow's services
Connecting the MCP to your client takes no auth (it's a read-only advisor). But the workflows it plans needyourcredentials for Gmail, Slack, Stripe, your CRM, and so on. For how to provision those safely — least-privilege scopes, secret managers, and managed-auth brokers — seedocs/CONNECTION_SETUP.md. OrchestrateMCP never holds a credential.
For source review packages, never zip the working folder directly. Usepnpm export:safe; seedocs/SAFE_EXPORT.mdfor the forbidden paths and archive inspection command.
orchestratekit-mcp/ src/ server.ts Entry point — wires MCP server to stdio transport config.ts Server name and version constants tools/ index.ts Tool registration (18 tools: health_check + 17 graph/advisor tools) composeWorkflowRoute.ts listGraphComponents.ts / getGraphComponent.ts listGraphEdges.ts / getGraphEdge.ts getStackRecommendation.ts listKnownRoutes.ts / getRoute.ts registry/ registryLoader.ts YAML loader with validation, status filtering, cross-ref checks componentSchema.ts / edgeSchema.ts / stackSchema.ts / routeSchema.ts / playbookSchema.ts registryTypes.ts / registryValidation.ts graph/ capabilityMatcher.ts Keyword + token matching: goal text → components routeComposer.ts Orchestrates all graph modules into a composed route routeScoring.ts Deterministic 0-100 score with breakdown routeOrdering.ts Topological sort via Kahn's algorithm safetyAugmenter.ts Auto-adds approval gates and audit log playbookOverlap.ts Detects overlap with known playbooks/routes docs-index/ Supplementary docs loader (future) lib/ errors.ts McpToolError class and toErrorResult helper logger.ts Stderr-only logger (stdout reserved for transport) registry/ components/ component YAML files (64 active) edges/ edge/relation YAML files (151 active) stacks/ stack YAML files routes/ route YAML files (13) playbooks/ golden-path playbook YAML files (14) docs-index/ Supplementary context documents examples/ cursor-mcp.json Example Cursor MCP config claude-desktop-config.json Example Claude Desktop config tests/ health-check.test.ts
- No first-party credential storage — it recommends secret managers / managed-auth brokers, never holds a secret
- No auth / OAuth / accounts — the hosted endpoint is read-only and stateless, nothing to log into
- No vector database
- No graph database (Neo4j etc.)
- No automatic registry updates
- No LLM API calls inside MCP tools
- No SaaS dashboard
- No dependency on OrchestrateLab at runtime
MAR-35 ✅ Scaffold — done MAR-37 ✅ Graph registry schemas: components, edges, stacks, routes, playbooks MAR-38 ✅ Seed workflow graph baseline MAR-77 ✅ Graph lookup tools: list/get components, edges, stacks, routes MAR-78 ✅ compose_workflow_route — deterministic route composer MAR-49 ✅ Benchmark setup — see docs/BENCHMARKING.md MAR-88 ✅ Domain-gated capability matcher — eliminates cross-domain false positives MAR-92 ✅ Registry lint + untested_edge_pct in health_check MAR-95 ✅ crm_note_write component + research→content bridge edge MAR-96 ✅ Benchmark protocol v2 — rubric, prompts-v2.yaml, PROTOCOL.md MAR-97 ✅ Docs truth pass — registry counts, tool count, verify path
Run the public, deterministic registry benchmark locally:
It runs seven fixed prompts with no LLM or network calls, checks required components and known false positives, fingerprints the inputs and registry, and prints every candidate status, untested edge, and compose-noise flag. See the currentmachine-readable and human-readable results.
This proves deterministic graph conformance, not model-quality uplift. The manual A/B/C protocol for comparing vanilla and MCP-assisted client responses remains available inbenchmarks/PROTOCOL.md; its archived scores retain their original isolation caveats and are not a current public headline.
Maintainers can intentionally refresh the committed result after reviewing a registry change:
pnpm benchmark:write pnpm benchmark:check
OrchestrateMCP is available under theMIT License.
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