Skip to main content
Glama
CJavierSaldana

MCP Ask-to-Code

MCP Ask-to-Code

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

Quick Install

# Global install with pipx (recommended)
pipx install git+https://github.com/cjaviersaldana/mcp-ask-to-code.git

# Or with pip
pip install git+https://github.com/cjaviersaldana/mcp-ask-to-code.git

Related MCP server: codex-cli-mcp-tool

Prerequisites

Claude Code CLI installed and authenticated:

npm install -g @anthropic-ai/claude-code

Usage

# Run (stdio mode for Claude Desktop)
mcp-ask-to-code

# Run with a specific model
mcp-ask-to-code --model claude-sonnet-4-20250514

# Run on a port (SSE mode for multiple sessions)
mcp-ask-to-code --port 8080

Options

Argument

Env Variable

Default

Description

--model

CLAUDE_MODEL

(CLI default)

Model to use (e.g. claude-sonnet-4-20250514, opus)

--name

MCP_NAME

Autonomous Code Agent

Server name

--tool-name

MCP_TOOL_NAME

ask_autonomous_agent

Tool function name

--command

CLAUDE_CMD

claude

Claude CLI binary path

--port

MCP_PORT

0 (stdio)

Port for SSE mode

--host

MCP_HOST

127.0.0.1

Host for SSE mode

Claude Desktop Configuration

Add to your config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Linux: ~/.config/claude-desktop/claude_desktop_config.json

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Basic Setup

{
  "mcpServers": {
    "ask-to-code": {
      "command": "mcp-ask-to-code",
      "args": []
    }
  }
}

With Specific Model

{
  "mcpServers": {
    "ask-to-code": {
      "command": "mcp-ask-to-code",
      "args": ["--model", "claude-sonnet-4-20250514"]
    }
  }
}

Custom "Expert" Personality

{
  "mcpServers": {
    "backend-expert": {
      "command": "mcp-ask-to-code",
      "args": ["--model", "opus", "--name", "Backend Architect"],
      "env": {
        "MCP_TOOL_NAME": "consult_backend_expert"
      }
    }
  }
}

Multiple Agents

{
  "mcpServers": {
    "code-agent": {
      "command": "mcp-ask-to-code",
      "args": ["--model", "claude-sonnet-4-20250514"]
    },
    "code-reviewer": {
      "command": "mcp-ask-to-code",
      "args": ["--model", "opus"],
      "env": {
        "MCP_NAME": "Code Reviewer",
        "MCP_TOOL_NAME": "review_code"
      }
    }
  }
}

How It Works

  1. Exposes a single tool (ask_autonomous_agent) to the LLM

  2. Delegates questions to Claude Code CLI with --dangerously-skip-permissions -p

  3. Returns clean output (ANSI codes stripped)

License

MIT

Available Tools

1 tool
ask_autonomous_agentA

AUTONOMOUS AGENT: Solves a coding task or answers a question by running an internal agent. This tool has full access to the filesystem, can run tests, read files, and analyze logic.

ParametersJSON Schema
NameRequiredDescriptionDefault
questionYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that the tool has full filesystem access, can run tests, read files, and analyze logic. This alerts the agent to significant capabilities and potential risks, though it does not explicitly mention side effects or destructive actions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no extraneous information. The first sentence states the core function, and the second adds critical behavioral context. Every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter and an existing output schema, the description adequately covers purpose and behavioral traits. It is missing usage guidelines and parameter elaboration, but given the simplicity, it is mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the single required parameter 'question'. The description provides no additional meaning, format, or constraints beyond the parameter name in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool solves a coding task or answers a question by running an internal agent. It specifies the resource (coding tasks/questions) and action (solving/answering). No siblings exist, so differentiation is not needed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for coding tasks and questions but provides no when-to-use or when-not-to-use guidance. While no siblings exist, there is no mention of alternatives or contexts where this tool is unsuitable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev0.1.2
    • First observedask_autonomous_agent

TDQS

A3.6/5.0
Disambiguation5/5

Only one tool exists, so there is no possibility of ambiguity or overlap.

Naming Consistency5/5

With a single tool, naming is trivially consistent; no pattern conflicts exist.

Tool Count2/5

One tool for a broad coding-assistance domain is extremely thin; typical servers have at least a few tools to separate concerns.

Completeness2/5

The single tool attempts to cover the entire domain, but users cannot compose or select finer-grained operations, leading to a black-box experience.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    An MCP server that integrates Google Gemini CLI with Claude Code for AI-powered development assistance, enabling code review, bug analysis, feature planning, and code explanation without requiring an API key.
    8
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that solves permission fatigue by letting you pre-approve commands, enabling Claude to run them without asking for permission each time.
    -

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/CJavierSaldana/mcp-ask-to-code'

If you have feedback or need assistance with the MCP directory API, please join our Discord server