C

Coding Tools MCP

Give any AI agent the ability to code

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  • UpdatedOct 29, 2026
  • Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time — check back soon.

Install Coding Tools MCP

Pick your client, then add it in one click or paste the config.

No confirmed install command yet

We only publish a config when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for coding-tools-mcp, and we’d rather show nothing than a guess you’d paste into your client.

Open setup steps on GitHub

Overview

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

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From the project README

Coding Tools MCP

English | 简体中文

Give any AI chat or agent a safe pair of hands on your codebase.

PyPI npm Python compliance release License

Coding Tools MCP is a model-neutral coding runtime served over the Model Context Protocol: file reading and search, structured multi-file patches, command execution, interactive sessions, and git — one server that any MCP client can drive. Claude Desktop, Claude Code, Codex, Cursor, Cline, VS Code, Windsurf, Gemini CLI, or an agent you build yourself gets the default catalog of 18 battle-tested tools, confined to one workspace and gated by permission modes.

Watch the demo

Why people use it

  • It turns a chat app into a coding agent. Claude Desktop — or any MCP chat client — gets real repo access with the subscription you already have. No extra product required.
  • Safety is the product, not an afterthought. One workspace root per server. Absolute paths, .. traversal, and symlink escapes are rejected. Permission modes gate network access, shell expansion, inline scripts, and destructive commands. On Linux, Landlock adds kernel-level filesystem confinement.
  • It is model- and vendor-neutral. A truthfully annotated, mode-aware catalog — no profile switching, no annotation games. Swap models or clients freely; the runtime contract stays put.
  • It is engineered for context windows. Results are summarized, paginated, and capped by design; serialized tool-result bytes dropped 37% release-over-release on the deterministic dogfood workload with unchanged task completion.

Quickstart

Run it with whichever toolchain you already have (the server is Python ≥ 3.11 from PyPI; the npm package is a thin launcher that starts it via uv or pipx):

bash
uvx coding-tools-mcp --stdio --workspace /path/to/repo   # Python toolchain
npx coding-tools-mcp --stdio --workspace /path/to/repo   # Node toolchain

Wire it into Claude Desktop, Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, or Cline — the JSON is the same everywhere (swap uvx for npx if you prefer Node):

config.json
{
  "mcpServers": {
    "coding-tools": {
      "command": "uvx",
      "args": ["coding-tools-mcp", "--stdio", "--workspace", "/path/to/repo"]
    }
  }
}

Then ask your client: "run the test suite and fix the first failure."

Prefer HTTP? Drop --stdio and the server speaks Streamable HTTP on http://127.0.0.1:8765/mcp. Both protocol eras are served on either transport: MCP 2026-07-28 in full, with tools as the only advertised capability, and the handshake era 2025-11-25 with 2025-06-18 compatibility. Neither has sessions. A one-line installer, per-client walkthroughs, and troubleshooting live in docs/quickstart.md and docs/mcp-client-config.md.

Seven things to try

1. Make Claude Desktop your coding agent. The config above is all it takes — the chat window you already pay for can now read, patch, test, and commit-review a real repository.

2. Code on your own machine from anywhere.

bash
CODING_TOOLS_MCP_AUTH_MODE=bearer ./integrations/tunnels/tunnel.sh cloudflared /path/to/repo

Loopback bind + authenticated HTTPS tunnel (cloudflared, ngrok, or Microsoft Dev Tunnel). Point claude.ai on your phone at https://<tunnel-host>/mcp and drive your home workstation from anywhere. ChatGPT and Grok connect through their connector settings the same way. Bearer tokens and OAuth 2.1 + PKCE (with RFC 7591 dynamic registration) are built in. → docs/remote-mcp.md

3. Let an agent loose on untrusted code — inside a disposable sandbox.

Terminal
docker build -t coding-tools-mcp-sandbox:local .
docker run --rm --init -it -p 8765:8765 -v "$PWD:/workspace" coding-tools-mcp-sandbox:local

A containerized server with toolchains and caches preconfigured, safe to point at a sketchy PR and destroy afterwards. → docs/docker.md

4. Spin up a cloud sandbox with one MCP call. The bundled Cloudflare Worker control plane exposes start_coding_tools_sandbox as an MCP tool: one call dispatches a GitHub Actions runner that boots the Docker sandbox and publishes it behind an authenticated Cloudflare Tunnel. Ephemeral compute, no server of your own.

5. Drive it from a GUI.

bash
python -m pip install "coding-tools-mcp[desktop]"
coding-tools-mcp-desktop

Per-workspace profiles, server and tunnel start/stop, credential setup with clipboard helpers, live health checks. English and 简体中文.

6. Keep an interactive command alive. exec_command starts a REPL or debugger under a real PTY; write_stdin feeds it across turns; read_output pages long output; kill_command cleans up. Long-running processes are first-class, with deadline watchdogs and bounded buffers.

7. Give your own agent production-grade hands. Building an agent loop with the Anthropic SDK or anything else? Don't hand-roll file and exec tools — speak MCP to this server and inherit the whole safety boundary. → docs/embedding.md

The tool catalog

The registry contains 19 truthfully annotated tools. The default safe and trusted modes advertise 18; dangerous also advertises request_permissions, the only mode in which that tool can grant anything. apply_patch and apply_changes are the file-mutation primitives: both are staged, baseline-checked, atomic across files, and support rollback.

GroupTools
Files & searchread_file · list_dir · list_files · search_text · apply_patch · apply_changes · view_image
Executionexec_command · write_stdin · read_output · kill_command · request_permissions (dangerous only)
Gitgit_status · git_diff · git_log · git_show · git_blame
Runtimeserver_info · check_exec_environment

Root AGENTS.md/CLAUDE.md files load automatically and come back in the instructions of initialize, or of server/discover for a client that never handshakes. Tool content is concise agent-facing text; structuredContent carries the complete machine result. Schemas and result envelopes: docs/tools-and-schemas.md · docs/runtime-contract-v0.3.md.

Safety Boundary

ModeMeant forWhat it allows
safe (default)day-to-day agent workfile tools and vetted commands; network-looking commands, shell expansion, inline scripts, and destructive commands all require explicit permission
trustedlocal developmentopens network, shell expansion, and inline scripts; keeps secret filtering and destructive-command checks
dangerousisolated containers/VMs onlydisables exec_command permission gates; workspace path boundaries still apply

Recursive listing and search exclude .git, node_modules, build outputs, virtualenvs, and caches. Commands run with workspace-bound cwd, scrubbed environment, timeouts, and output caps. Linux hosts with Landlock get kernel-enforced filesystem confinement; other platforms get an explicit warning — this is still not a complete OS sandbox, so use the Docker image or a VM for genuinely untrusted work. Details: SECURITY.md · docs/security-boundary.md · docs/permission-modes.md

Telemetry

The server sends anonymous usage telemetry (per-tool success/latency counters and version/platform dimensions — never paths, arguments, commands, or file contents) to help prioritize fixes. Disable it with CODING_TOOLS_MCP_TELEMETRY=off or DO_NOT_TRACK=1; it is automatically off in CI. CODING_TOOLS_MCP_TELEMETRY=debug prints every event to stderr instead of sending. The full event list and guarantees are in docs/telemetry.md.

Evidence, Dogfood and SWE-bench

Every release ships through a tag-triggered pipeline in which the compliance suite, real-workload benchmark, and SWE-bench harness run from the same commit that publishes to PyPI and npm — both via trusted publishing, npm with provenance. Dogfood efficiency metrics are reproducible (make dogfood-smoke) and checked in under reports/. This repository does not claim a model-generated SWE-bench leaderboard result — see docs/swe-bench.md for exactly what is and is not measured. More: COMPLIANCE.md · BENCHMARK.md · docs/dogfood.md

Documentation

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Frequently Asked Questions about Coding Tools MCP

We don't have a confirmed install command for coding-tools-mcp yet, so we don't publish a generated one — a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/xyTom/coding-tools-mcp) for the current steps.

Give any AI agent the ability to code

We don't have confirmed pricing for coding-tools-mcp. Listing it on AllMCPs is free, but that says nothing about what the server itself costs — check the project's own site for current pricing.

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