MCP Servers

cctx-mcp

An MCP server that provides structure-aware code analysis (symbol trees, dependencies, docs) to reduce AI agent token consumption by up to 99%, along with Git commit intelligence.

README

Cut AI agent token usage by 87%. Structure-aware code analysis via the <a href="https://modelcontextprotocol.io">Model Context Protocol</a> — returns symbol trees, dependencies, and docs instead of raw file contents.

Overview

CCTX-MCP — Code ConTeXt via Model Context Protocol. An MCP server that gives AI agents a structured view of source code without reading entire files.

Built for Claude, Cursor, OpenCode, and any MCP-compatible AI coding tool.

<code>uvx cctx-mcp</code> · <a href="#%EF%B8%8F-tools">Tools</a> · <a href="#-token-savings">Savings</a> · <a href="#-install">Install</a>

Quick Start

uvx cctx-mcp

Add to your MCP client config:

{
  "mcpServers": {
    "cctx-mcp": {
      "command": "uvx",
      "args": ["cctx-mcp"]
    }
  }
}

Tools

Code Analysis

Tool	Returns	Replaces	Savings
`smart_read`	symbol hierarchy, deps, docs, line counts	`cat` + manual parsing	~87%
`find_symbols`	symbol locations by name or type	`grep -r` + file reads	~99%
`get_dependencies`	all imports of a file in one shot	`grep ^import`	~96%
`trace_calls`	every call site with file + line	`grep` across repo	~90%
`analyze_project`	language breakdown, file counts, tree	`find` + `wc`	~98%
`get_symbol_summaries`	AI semantic descriptions per symbol	reading implementation	~85%

Git & Commits

Tool	Returns	Replaces	Savings
`compact_change_intelligence`	structured git diff with intent cues	`git diff` + `git status`	~75%
`draft_commit`	AI-generated conventional commit message	writing from scratch	~90%
`approve_commit_draft`	executes the commit after review	`git add` + `git commit`	—

Observability

get_config · get_health · get_version

Token Savings

Operation	Native	With CCTX-MCP	Savings
Read 500-line file	~1,500 tokens	~200 tokens	87%
Find function across project	~5,000 tokens	~50 tokens	99%
Understand imports	~800 tokens	~30 tokens	96%
Analyze project structure	~10,000 tokens	~150 tokens	98%
Git change summary	~3,000 tokens	~750 tokens	75%

Typical session: 80%+ aggregate savings.

Supported Languages

Install

uvx (recommended)

{
  "mcpServers": {
    "cctx-mcp": {
      "command": "uvx",
      "args": ["cctx-mcp"]
    }
  }
}

pip

pip install cctx-mcp

{
  "mcpServers": {
    "cctx-mcp": {
      "command": "python",
      "args": ["-m", "code_context.server"]
    }
  }
}

source

git clone https://github.com/nikondrat/cctx-mcp.git
cd cctx-mcp
uv sync
uv run python -m code_context.server --skip-index

Configuration

Variable	Default	Description
`CC_OLLAMA_URL`	`http://localhost:11434`	Ollama server address
`CC_OPENROUTER_API_KEY`	—	Remote inference key
`CC_LLM_ROUTER`	`local-first`	`local-first`, `local-only`, `remote-first`, `remote-only`
`CC_COMMIT_MODEL`	`gemma4:latest`	Local model for commit drafting
`CC_EMBED_MODEL`	`nomic-embed-text`	Local model for embeddings
`CC_SEMANTIC_SUMMARIES`	`1`	Enable AI symbol summaries

Development

uv sync
uv run pytest tests/ -v

Debug Logging

Tool calls are logged to ~/.code-context-cache/debug.jsonl with args, result preview, latency, and status:

tail -f ~/.code-context-cache/debug.jsonl

Set CC_DEBUG_LOG env var to change the log path.

PRs welcome. Open issues.

License

MIT — free for any use.

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