contextforge-mcp

MCP orchestrator combining codebase-memory-mcp + headroom + Spec Kit into a single pipeline.

Agent (Claude Code / Cursor / Codex)
  │
  ▼
contextforge-mcp  ←── single MCP server
  │
  ├── codebase-memory-mcp  (knowledge graph: 99% fewer retrieval tokens)
  ├── headroom             (compression: 60–95% fewer prompt tokens)
  └── Spec Kit             (SDD workflow: spec → plan → tasks → implement)

---

Install

# Prerequisites
npm install -g codebase-memory-mcp
pip install "headroom-ai[all]"
pip install spec-kit

# Install contextforge-mcp
pip install contextforge-mcp

Setup

# Health check
contextforge-mcp doctor

# Configure Claude Code (writes .mcp.json)
contextforge-mcp install --target claude

# Configure Spec Kit extension
contextforge-mcp install --target speckit

# Both at once
contextforge-mcp install --target all

Usage in Claude Code

# 1. Index the codebase (once per session)
cbm_index_repository(repo_path=".")

# 2. Query the graph (instead of grep/read)
cbm_search_graph(name_pattern=".*Payment.*")
cbm_trace_path(function_name="processPayment")
cbm_get_architecture()

# 3. Check token savings
cf_stats()

Spec Kit workflow

/speckit.constitution
/speckit.specify
/speckit.cf-analyze      ← analyze codebase before planning
/speckit.plan
/speckit.tasks
/speckit.cf-index        ← index before implementing
/speckit.cf-implement    ← graph-aware implementation
/speckit.cf-stats        ← token savings report

Tools (23 total)

Prefix	Count	Description
cbm_*	14	codebase-memory-mcp graph tools
cf_*	9	ContextForge meta + Spec Kit tools

Environment variables

Variable	Default	Description
CBM_BINARY_PATH	auto	Path to codebase-memory-mcp binary
CF_MODEL	claude-sonnet-4-6	Model hint for headroom
CF_LOG_LEVEL	WARNING	Log level

Credits

• codebase-memory-mcp — MIT
• headroom — Apache 2.0
• spec-kit — MIT

License

MIT