any-script-mcp

any-script-mcp

An MCP server that exposes arbitrary CLI tools and shell scripts as MCP Tools

日本語版

Overview

An MCP server that publishes commands defined in YAML files as MCP Tools. By defining tools in a configuration file, you can execute arbitrary shell scripts from MCP clients.

Installation

npx

Claude Code:

$ claude mcp add any-script \
  -s user \
  -- npx any-script-mcp

json:

{
  "mcpServers": {
     "any-script": {
       "command": "npx",
       "args": ["any-script-mcp"]
     }
  }
}

Configuration

Create a configuration file at $XDG_CONFIG_HOME/any-script-mcp/config.yaml (typically ~/.config/any-script-mcp/config.yaml).

You can also specify custom configuration file paths using the ANY_SCRIPT_MCP_CONFIG environment variable:

# Single configuration file
$ ANY_SCRIPT_MCP_CONFIG=/path/to/custom/config.yaml npx any-script-mcp

# Multiple configuration files (Unix/macOS - separated by colon)
$ ANY_SCRIPT_MCP_CONFIG=/path/to/custom.yaml:$XDG_CONFIG_HOME/any-script-mcp/config.yaml npx any-script-mcp

# Multiple configuration files (Windows - separated by semicolon)
$ ANY_SCRIPT_MCP_CONFIG=C:\path\to\custom.yaml;%APPDATA%\any-script-mcp\config.yaml npx any-script-mcp

When multiple configuration files are specified:

• All tools from all files are merged into a single collection
• If the same tool name appears in multiple files, the first occurrence takes precedence
• At least one valid configuration file must be successfully loaded
• This is useful for separating common tools from project-specific or personal customizations

Testing Your Configuration

You can test your configuration using the MCP Inspector:

$ npx @modelcontextprotocol/inspector npx any-script-mcp

This will open a web interface where you can see your registered tools and test them interactively.

Example Configuration

# yaml-language-server: $schema=https://raw.githubusercontent.com/izumin5210/any-script-mcp/main/config.schema.json
tools:
  - name: echo
    description: Echo a message
    inputs:
      message:
        type: string
        description: Message to echo
    run: |
      echo "Received: $INPUTS__MESSAGE"
      
  - name: git_status
    description: Check git status with optional branch
    inputs:
      branch-name:
        type: string
        description: Branch to check out
        required: false
      verbose:
        type: boolean
        description: Show verbose output
        default: false
    run: |
      if [ -n "${INPUTS__BRANCH_NAME:-}" ]; then
        git checkout "$INPUTS__BRANCH_NAME"
      fi
      
      if [ "$INPUTS__VERBOSE" = "true" ]; then
        git status -v
      else
        git status
      fi
      
  # Delegate search to codex CLI. Inspired by https://github.com/yoshiko-pg/o3-search-mcp
  - name: codex-search
    description: AI agent with web search for researching latest information, troubleshooting program errors, discussing complex problems and design decisions, exploring advanced library usage, and investigating upgrade paths. Supports natural language queries.
    inputs:
      prompt:
        type: string
        description: What you want to search, analyze, or discuss with the AI agent
    run: |
      codex exec \
        --model gpt-5 \
        --sandbox workspace-write \
        --config "sandbox_workspace_write.network_access=true" \
        "$INPUTS__PROMPT" \
        --json \
        | jq -sr 'map(select(.msg.type == "agent_message") | .msg.message) | last'
    timeout: 600000  # 10 minutes for complex AI operations
      
  - name: build
    description: Run build process with tests
    run: |
      npm run build
      npm test
    timeout: 180000  # 3 minutes for build and test

Configuration Format

Tool Definition

Each tool has the following fields:

• name: Tool name (alphanumeric, underscore, and hyphen only)
• description: Tool description
• inputs: Input parameter definitions (object format)
• run: Shell script to execute
• shell: Shell command to execute the script (optional, default: "bash -e {0}")
• timeout: Execution timeout in milliseconds (optional, default: 300000 = 5 minutes)

Input Parameters

Each input parameter has the following fields:

• type: Parameter type (string, number, boolean)
• description: Parameter description
• required: Whether the parameter is required (default: true)
• default: Default value (optional)

Input parameters are passed as environment variables to shell scripts in two ways:

Individual Environment Variables

Variable names have the INPUTS__ prefix and are converted to uppercase (hyphens are converted to underscores).

Examples:

• message → $INPUTS__MESSAGE
• branch-name → $INPUTS__BRANCH_NAME

JSON Format (INPUTS_JSON)

All inputs are also available as a single JSON object in the INPUTS_JSON environment variable. This preserves type information, making it easier to work with non-shell interpreters.

Example usage:

// Node.js
const inputs = JSON.parse(process.env.INPUTS_JSON);
console.log(inputs.num * 2); // count is a number, not a string

Shell Option

The shell option allows you to specify a custom shell or interpreter for executing scripts. The {0} placeholder is replaced with the path to the temporary script file.

Default: "bash -e {0}"

Examples:

# yaml-language-server: $schema=https://raw.githubusercontent.com/izumin5210/any-script-mcp/main/config.schema.json
tools:
  # Python script
  - name: python_analysis
    description: Analyze data with Python
    shell: "python {0}"
    inputs:
      data:
        type: string
        description: Data to analyze
    run: |
      import os
      import json
      
      data = os.environ['INPUTS__DATA']
      # Process data with Python
      result = {"analysis": f"Processed: {data}"}
      print(json.dumps(result))

  # Deno script
  - name: deno_fetch
    description: Fetch data with Deno
    shell: "deno run --allow-net {0}"
    inputs:
      endpoint:
        type: string
        description: API endpoint
    run: |
      const endpoint = Deno.env.get("INPUTS__ENDPOINT");
      const response = await fetch(endpoint);
      console.log(await response.json());
  
  # Using INPUTS_JSON for type preservation
  - name: add_2
    description: add 2 to a number
    shell: "node {0}"
    inputs:
      num:
        type: number
        description: a number to add 2 to
    run: |
      const inputs = JSON.parse(process.env.INPUTS_JSON);
      console.log(inputs.num + 2); // number is a number, not a string

Advanced Examples - AI Agents with Web Search

# yaml-language-server: $schema=https://raw.githubusercontent.com/izumin5210/any-script-mcp/main/config.schema.json
tools:
  - name: gemini-search
    description: AI agent with web search using Gemini 2.5 Flash
    shell: "deno run -N -E {0}"
    inputs:
      query:
        type: string
        description: Query for AI search
        required: true
    run: |
      import { GoogleGenAI } from "npm:@google/genai@^1";
      const inputs = JSON.parse(Deno.env.get("INPUTS_JSON"));
      const ai = new GoogleGenAI({ apiKey: Deno.env.get("GEMINI_API_KEY") });
      const res = await ai.models.generateContent({
        model: "gemini-2.5-flash",
        contents: inputs.query,
        config: {
          tools: [{ googleSearch: {} }],
          systemInstruction: "...",
        },
      });
      console.log(
        res.candidates?.[0]?.content?.parts?.map((p) => p.text ?? "").join(""),
      );

  - name: gpt-5-search
    description: AI agent with web search using GPT-5
    shell: "deno run -N -E {0}"
    inputs:
      query:
        type: string
        description: Query for AI search
        required: true
    run: |
      import OpenAI from "jsr:@openai/openai";
      const inputs = JSON.parse(Deno.env.get("INPUTS_JSON"));
      const client = new OpenAI({ apiKey: Deno.env.get("OPENAI_API_KEY") });
      const res = await client.responses.create({
        model: "gpt-5",
        tools: [{ type: "web_search_preview" }],
        input: inputs.query,
        instructions: "...",
      });
      console.log(res.output_text);

License

MIT