# Claude Code Bridge

> Use this tool when you need to integrate AI-driven code analysis and processing into your workflow, solving problems such as automated code reviews, searches, and structured output generation. It exposes CLI capabilities as MCP tools, accepting queries and code inputs and producing outputs through a subprocess, with support for concurrent invocations and configurable model selection. This enables efficient and scalable code processing, making it ideal for use cases requiring automated code inspection and generation.

Canonical page: https://skillsregistry.net/skills/hampsterx-claude-code-bridge  
JSON: https://api.skillsregistry.net/v1/skills/hampsterx-claude-code-bridge

## Description

Exposes Claude Code CLI capabilities as MCP tools, enabling AI agents to run queries, code reviews, searches, and structured outputs through a Claude Code subprocess. Supports concurrent invocations, configurable model selection per tool type, and optional API key forwarding.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/hampsterx-claude-code-bridge)
- **Repository:** <https://github.com/hampsterx/claude-mcp-bridge>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "hampsterx-claude-code-bridge"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hampsterx-claude-code-bridge` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hampsterx-claude-code-bridge/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt