contextforge-mcp
Integrates Spec Kit for a structured SDD workflow: define specifications, plan, generate tasks, and implement with graph-aware indexing.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@contextforge-mcpIndex codebase and show architecture overview"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
contextforge-mcp
MCP compression middleware that connects codebase-memory-mcp + headroom + Spec Kit into a unified, token-efficient workflow.
Architecture
Claude Code
├── codebase-memory-mcp ← graph queries (cbm_* tools)
│ │
│ └── large result
│ │
└── contextforge-mcp ← YOU ARE HERE
│
cf_compress_cbm(result, tool_name)
│
└── compressed result (60-95% fewer tokens)ContextForge does NOT proxy codebase-memory-mcp — both servers run independently. The agent calls CBM for graph queries, then passes results through ContextForge for compression. This design is reliable, cross-platform, and works with any MCP client.
Related MCP server: ContextAtlas
Install
npm install -g codebase-memory-mcp
pip install "headroom-ai[all]"
pip install contextforge-mcpSetup
# Health check
contextforge-mcp doctor
# Configure Claude Code (writes .mcp.json with both servers)
contextforge-mcp install --target claudeWorkflow
# 1. Query the graph (via codebase-memory-mcp)
result = cbm_search_graph(name_pattern=".*Payment.*", label="Function")
# 2. Compress the result (via contextforge-mcp)
compressed = cf_compress_cbm(result=result, tool_name="search_graph")
# → [ContextForge ✓ search_graph: 8420→612 tokens (93% saved in 45ms)]
# 3. Use compressed result in your context
# 4. Check savings
cf_stats()Tools (9 total)
Compression
Tool | Description |
| Compress CBM tool output |
| Compress arbitrary text |
Stats
Tool | Description |
| Session token savings + cost estimate |
| Reset session counters |
Spec Kit
Tool | Description |
| Compressed spec.md |
| Compressed plan.md |
| Compressed tasks.md |
| Any artifact |
| Full bundle (spec+plan+tasks) |
| List all features + phase |
Supported CBM tool names for cf_compress_cbm
search_graph · search_code · get_architecture · find_dead_code · find_similar_code · get_impact · trace_path · trace_call_path · cypher_query · get_cross_service_links · get_node_details
Add to CLAUDE.md
## ContextForge MCP — Compression Workflow
After EVERY codebase-memory-mcp tool call that returns a large result,
immediately call cf_compress_cbm(result, tool_name) to compress it.
| CBM Query | Then compress with |
|-----------|-------------------|
| cbm_search_graph(…) | cf_compress_cbm(result, "search_graph") |
| cbm_get_architecture() | cf_compress_cbm(result, "get_architecture") |
| cbm_search_code(…) | cf_compress_cbm(result, "search_code") |
| cbm_trace_path(…) | cf_compress_cbm(result, "trace_path") |
| cbm_get_impact(…) | cf_compress_cbm(result, "get_impact") |
Call cf_stats() at end of session to measure total savings.Credits
codebase-memory-mcp — MIT
headroom — Apache 2.0
spec-kit — MIT
License
MIT
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