README.md
LLM-powered on-demand tool generation with human-in-the-loop approval
JIT Tool Synthesis v3
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-5.4, Codex 5.3
- 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-4-5-sonnet
# Option 2: OpenAI direct
LLM_API_KEY=sk-...
LLM_BASE_URL=https://api.openai.com/v1
LLM_MODEL=gpt-4o
# Option 3: Ollama (local)
LLM_BASE_URL=http://localhost:11434/v1
LLM_MODEL=llama3.1
# Option 4: Groq
LLM_API_KEY=gsk_...
LLM_BASE_URL=https://api.groq.com/openai/v1
LLM_MODEL=llama-3.1-70b-versatile
Usage
Start the MCP Server
npm run build
node dist/server.js
Runtime Configuration
You can change the LLM provider without restarting:
# View current config
get_config
# Change model at runtime
set_config model=openai/gpt-4o
MCP Tools
| Tool | Description |
|---|---|
synthesize_tool |
Generate a new tool from natural language |
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
- Request — User asks for a tool (e.g., "create a weather fetcher")
- Synthesize — LLM generates tool code
- Approve — Human reviews and approves the code
- Execute — Tool runs in sandboxed environment
- Store — Approved tools persist in registry
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-3-5-sonnet-20241022 |
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.
Tools (10)
synthesize_toolGenerate a new tool from natural languageapprove_toolActivate a pending toolreject_toolDiscard a pending toolexecute_toolRun an approved toollist_generated_toolsList all approved toolsget_toolView tool detailsremove_toolDelete a toollist_pendingList tools waiting for approvalget_configView LLM configurationset_configChange LLM provider/model at runtimeEnvironment Variables
LLM_API_KEYrequiredAPI key for your providerLLM_BASE_URLAPI endpointLLM_MODELModel to useConfiguration
claude_desktop_config.json
{"mcpServers": {"jit-tool-synthesis": {"command": "node", "args": ["/path/to/jit-tool-synthesis/dist/server.js"], "env": {"LLM_API_KEY": "your-key-here"}}}}Try it
→Create a tool that fetches the current weather for a given city.
→List all the tools I have generated so far.
→Approve the pending tool with ID 123.
→Execute the weather fetcher tool for New York.
→Change the LLM model to gpt-4o.