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Thebeatkicks

OrchestrateKit MCP

by Thebeatkicks
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TypeScript
Local

OrchestrateKit MCP

Local stdio MCP server that gives Cursor and Claude Desktop access to an opinionated, evidence-backed workflow graph for designing production-ready AI workflows.

Status: Scaffold with stub registry loader (MAR-35 graph-ready). Schemas, full registry data and graph tools are added in subsequent issues.

What it does

OrchestrateKit MCP exposes a structured registry of:

components  →  the building blocks of AI workflows
edges       →  tested relations between components (requires, safer_with, conflicts_with, …)
stacks      →  opinionated technology choices for different deployment contexts
routes      →  tested paths through the component graph
playbooks   →  golden-path routes with full implementation guidance

When a user describes a workflow goal, the MCP can:

  1. Match the goal to required capabilities and components.

  2. Traverse tested component relationships.

  3. Reuse sections of known golden-path playbooks.

  4. Compose a candidate route when no exact playbook exists.

  5. Score route confidence (coverage, tested edges, stack fit, safety, simplicity).

  6. Return the route as structured implementation context for Cursor or Claude.

Related MCP server: AI PC Assistant MCP Server

What works right now

  • MCP server starts on stdio and responds to the health_check tool.

  • health_check returns { name, version, registry: { component_count, edge_count, stack_count, route_count, playbook_count } }.

  • Registry loader stub returns zero counts — real data is added in MAR-38.

  • pnpm verify (typecheck + tests) passes from a clean install.

Requirements

  • Node.js ≥ 20

  • pnpm

Local setup

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 from stdin and writes JSON-RPC to stdout. All log output goes to stderr.

Connect from Cursor

Copy examples/cursor-mcp.json content into your Cursor workspace MCP config at .cursor/mcp.json. Replace the cwd value with the absolute path to this directory.

{
  "mcpServers": {
    "orchestratekit": {
      "command": "npx",
      "args": ["tsx", "src/server.ts"],
      "cwd": "/absolute/path/to/orchestratekit-mcp"
    }
  }
}

Connect from Claude Desktop

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "orchestratekit": {
      "command": "npx",
      "args": ["tsx", "src/server.ts"],
      "cwd": "/absolute/path/to/orchestratekit-mcp"
    }
  }
}

Scripts

Script

Description

pnpm dev

Run server directly with tsx (no build step)

pnpm build

Compile to dist/ with tsup

pnpm typecheck

TypeScript type-check only (no emit)

pnpm test

Run unit tests with vitest

pnpm verify

Run typecheck then test

Project structure

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 (health_check + 8 graph 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 (added in MAR-38)
    edges/                  Edge/relation YAML files (added in MAR-38)
    stacks/                 Stack YAML files (added in MAR-38)
    routes/                 Route YAML files (added in MAR-38)
    playbooks/              Golden-path playbook YAML files (added in MAR-38)

  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

Non-goals (this phase)

  • No remote hosting

  • No auth / OAuth

  • 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

Build order

MAR-35  ✅  Scaffold — done
MAR-37  ✅  Graph registry schemas: components, edges, stacks, routes, playbooks
MAR-38  ✅  Seed workflow graph: 30 components, 47 edges, 1 stack, 5 playbooks
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

Benchmarking

To validate that the workflow graph improves planning quality over vanilla Cursor/Claude, run the manual benchmark described in docs/BENCHMARKING.md.

Quick start:

# Print session guide with route previews for all 7 prompts
pnpm tsx scripts/benchmark-template.ts

# Single prompt
pnpm tsx scripts/benchmark-template.ts p6_email_lead_crm

Results go in benchmarks/results-YYYY-MM-DD.md.

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