Skip to main content
Glama
deenesjakoruzh
EyeSeeThru

JIT Tool Synthesis

by EyeSeeThru
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

JIT Tool Synthesis v4

LLM-powered on-demand tool generation with human-in-the-loop approval and safe execution.

Overview

This system generates TypeScript tools dynamically using an LLM, requires human approval before execution, and runs them in a sandboxed environment.

Architecture

┌─────────────┐     ┌──────────────┐     ┌─────────────┐
│ Synthesizer │────▶│   Approval   │────▶│  Sandbox    │
│   (LLM)     │     │ (Human Gate) │     │ (Execution) │
└─────────────┘     └──────────────┘     └─────────────┘
       │                   │                    │
       ▼                   ▼                    ▼
  Generates TS        Waits for            Runs in
  tool code          human approval       isolated env

Components

File

Purpose

synthesizer.ts

Generates tool code using any OpenAI-compatible LLM

approval.ts

Human-in-the-loop gate — requires approval before execution

sandbox.ts

Safe execution environment for generated code

registry.ts

Tool persistence and storage

server.ts

MCP server integration

config.ts

Runtime configuration management

Provider-Agnostic

This tool works with any OpenAI-compatible LLM API:

  • OpenRouter — 100+ models (Claude, GPT, Llama, etc.)

  • OpenAI — GPT-4o, o3, etc.

  • Ollama — Local models (Llama, Qwen, etc.)

  • LM Studio — Local models with GUI

  • Groq — Fast inference

  • Any other OpenAI-compatible API

Setup

# Install dependencies
npm install

# Copy environment template
cp .env.example .env

Configure Your LLM Provider

Edit .env with your provider details:

# Option 1: OpenRouter (default - 100+ models)
LLM_API_KEY=your-openrouter-key
LLM_BASE_URL=https://openrouter.ai/api/v1
LLM_MODEL=anthropic/claude-sonnet-4-6

# Option 2: OpenAI direct
LLM_API_KEY=sk-...
LLM_BASE_URL=https://api.openai.com/v1
LLM_MODEL=gpt-5.4

# Option 3: Ollama (local)
LLM_BASE_URL=http://localhost:11434/v1
LLM_MODEL=llama-3.3

# Option 4: Groq
LLM_API_KEY=gsk_...
LLM_BASE_URL=https://api.groq.com/openai/v1
LLM_MODEL=llama-3.3-70b-versatile

Usage

Build

npm run build

Test with MCP Inspector

The fastest way to verify everything works:

npx @modelcontextprotocol/inspector node dist/server.js

Connect to MCP Clients

This server works with any MCP client. Example configs:

Claude Desktop — add to your Claude Desktop MCP settings:

{
  "mcpServers": {
    "jit-tool-synthesis": {
      "command": "node",
      "args": ["/absolute/path/to/jit-tool-synthesis/dist/server.js"],
      "env": {
        "LLM_API_KEY": "your-api-key",
        "LLM_BASE_URL": "https://openrouter.ai/api/v1",
        "LLM_MODEL": "anthropic/claude-sonnet-4-6"
      }
    }
  }
}

Claude Code:

claude mcp add jit-tools node /absolute/path/to/jit-tool-synthesis/dist/server.js

VS Code (Copilot):

code --add-mcp '{"name":"jit-tools","type":"stdio","command":"node","args":["/absolute/path/to/jit-tool-synthesis/dist/server.js"]}'

Cursor — add to .cursor/mcp.json:

{
  "mcpServers": {
    "jit-tools": {
      "command": "node",
      "args": ["/absolute/path/to/jit-tool-synthesis/dist/server.js"],
      "env": { "LLM_API_KEY": "your-api-key" }
    }
  }
}

Runtime Configuration

You can change the LLM provider without restarting:

# View current config
get_config

# Change model at runtime
set_config model=openai/gpt-5.4

MCP Tools

Tool

Description

synthesize_tool

Generate a new tool from natural language

test_tool

Test a pending tool with sample params before approval

approve_tool

Activate a pending tool

reject_tool

Discard a pending tool

execute_tool

Run an approved tool

list_generated_tools

List all approved tools

get_tool

View tool details

remove_tool

Delete a tool

list_pending

List tools waiting for approval

get_config

View LLM configuration

set_config

Change LLM provider/model at runtime

Workflow

  1. Request — User asks for a tool (e.g., "create a color converter")

  2. Synthesize — LLM generates tool code

  3. Test — Validate with sample params before committing

  4. Approve — Human reviews and approves the code

  5. Execute — Tool runs in sandboxed environment

  6. Store — Approved tools persist across sessions

Environment Variables

Variable

Description

Default

LLM_API_KEY

API key for your provider

(required for cloud)

LLM_BASE_URL

API endpoint

https://openrouter.ai/api/v1

LLM_MODEL

Model to use

anthropic/claude-sonnet-4-6

Also supported (legacy): OPENROUTER_API_KEY, OPENAI_API_KEY, OPENAI_BASE_URL, SYNTHESIZER_MODEL

Security

  • Generated code runs in isolated VM sandbox

  • Blocked patterns prevent dangerous code (process, require, eval, etc.)

  • API keys not stored in config file

Status

Production Ready — Phase 1 complete.

Install Server
F
license - not found
C
quality
C
maintenance

How are these scores calculated?

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

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

Tools

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/EyeSeeThru/jit-tool-synthesis'

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