Pincer-MCP
A security-hardened MCP gateway that enables AI agents to call LLM APIs (Gemini, OpenAI, Claude, etc.) using ephemeral proxy tokens, eliminating exposure of real API keys.
README
Pincer MCP ๐ฆ
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Pincer-MCP is a security-hardened Model Context Protocol (MCP) gateway that eliminates the "Lethal Trifecta" vulnerability in agentic AI systems. By acting as a stateless intermediary, Pincer ensures agents never see your real API keys.
๐ The Problem
Current AI agents store long-lived API keys in plain-text .env files or local databases. If compromised via prompt injection or host intrusion, attackers gain direct access to your:
- Database passwords
- Third-party API keys
โจ The Solution: Proxy Token Architecture
Pincer implements a "blindfold" security model:
- Agent knows: Only a unique proxy token (
pxr_abc123...) - Pincer knows: Mapping of proxy tokens โ real API keys (encrypted in OS keychain)
- Agent never sees: The actual credentials
sequenceDiagram
participant Agent
participant Pincer
participant Vault (OS Keychain)
participant External API
Agent->>Pincer: tools/call + proxy_token: pxr_abc123
Pincer->>Vault: Decrypt real API key
Vault-->>Pincer: gemini_api_key: AIzaSy...
Pincer->>External API: API call with real key
External API-->>Pincer: Response
Pincer->>Pincer: Scrub key from memory
Pincer-->>Agent: Response (no credentials)
๐ฆ Available Tools
gemini_generate: Secure Google Gemini API calls.openai_chat: Chat completions with OpenAI GPT models (gpt-4o, gpt-4-turbo, gpt-3.5-turbo, etc.).openai_list_models: List all available OpenAI models.openai_compatible_chat: Chat completions with any OpenAI-compatible API (Azure OpenAI, Ollama, vLLM, etc.).openai_compatible_list_models: List models from custom OpenAI-compatible endpoints.claude_chat: Chat completions with Anthropic Claude models (Claude 3.5 Sonnet, Opus, Haiku).openrouter_chat: Unified API access to 100+ models from multiple providers (OpenAI, Anthropic, Google, Meta, etc.).openrouter_list_models: List all available models across OpenRouter providers.openwebui_chat: OpenAI-compatible interface for self-hosted LLMs.openwebui_list_models: Discover available models on an OpenWebUI instance.gpg_sign_data: Sign data or files using a GPG/PGP private key stored in Pincer's vault. (Keyless Execution โ agent never sees the key)gpg_decrypt: Decrypt PGP-encrypted data using a vault-stored private key.
๐ GPG Key Management
# Generate a new GPG keypair (private key stored in vault)
pincer key generate --name "Release Signing" --email dev@example.com
# Import an existing PGP private key
pincer key import ./my-key.asc --passphrase "my-passphrase"
# List all stored GPG keys
pincer key list
# Export public key (safe to share)
pincer key export <key-id>
# Authorize an agent for signing
pincer agent authorize mybot gpg_sign_data --key <key-id>
(More callers coming soon!)
๐ Quick Start
Prerequisites
- Node.js 18+
- macOS, Windows, or Linux with native keychain support
Installation
Option 1: Global Installation (Recommended)
npm install -g pincer-mcp
# Now 'pincer' command is available system-wide
Option 2: Local Development
git clone https://github.com/VouchlyAI/Pincer-MCP.git
cd Pincer-MCP
npm install
npm run build
npm link # Makes 'pincer' command available locally
Setup Vault
# 1. Initialize vault (creates master key in OS keychain)
pincer init
# 2. Store your real API keys (encrypted)
pincer set gemini_api_key "AIzaSyDpxPq..."
pincer set openai_api_key "sk-proj-..."
# 3. Register an agent and generate proxy token
pincer agent add openclaw
# Output: ๐ซ Proxy Token: pxr_V1StGXR8_Z5jdHi6B-myT
# 4. Authorize the agent for specific tools
pincer agent authorize openclaw gemini_generate
Multi-Key Support
Store multiple keys for the same tool and assign them to different agents:
# Store two different Gemini API keys
pincer set gemini_api_key "AIzaSy_KEY_FOR_CLAWDBOT..." --label key1
pincer set gemini_api_key "AIzaSy_KEY_FOR_MYBOT..." --label key2
# View all stored keys
pincer list
# Assign specific keys to each agent
pincer agent add clawdbot
pincer agent authorize clawdbot gemini_generate --key key1
pincer agent add mybot
pincer agent authorize mybot gemini_generate --key key2
# View agent permissions
pincer agent list
Result: clawdbot uses key1, mybot uses key2 - perfect for rate limiting or cost tracking!
Run the Server
npm run dev
Configure Your Agent
Give your agent the proxy token (not the real API key):
export PINCER_PROXY_TOKEN="pxr_V1StGXR8_Z5jdHi6B-myT"
Tool-to-Secret Name Mappings
When storing secrets, you must use the correct secret name for each tool. See the Tool Mappings Guide for a complete reference.
When you run pincer agent authorize myagent gemini_generate, Pincer will inject the gemini_api_key secret when that tool is called.
Make a Tool Call
Your agent sends requests with the proxy token in the body:
{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "gemini_generate",
"arguments": {
"prompt": "Hello world",
"model": "gemini-2.0-flash"
},
"_meta": {
"pincer_token": "pxr_V1StGXR8_Z5jdHi6B-myT"
}
}
}
Pincer maps the proxy token to the real API key and executes the call securely.
๐๏ธ Architecture
Two-Tiered Vault System
Tier 1: Master Key (OS Keychain)
- Stored in macOS Keychain, Windows Credential Manager, or GNOME Keyring
- Never touches the filesystem
- Accessed only for encryption/decryption
Tier 2: Encrypted Store (SQLite)
- Database at
~/.pincer/vault.db - Three tables:
secrets: Real API keys (AES-256-GCM encrypted)proxy_tokens: Proxy token โ Agent ID mappingsagent_mappings: Agent ID โ Tool authorization
Authentication Flow
Request (_meta.pincer_token: pxr_xxx)
โ
Gatekeeper: Extract proxy token from body
โ
Vault: Resolve pxr_xxx โ agent_id โ tool_name โ real_api_key
โ
Injector: JIT decrypt & inject real key
โ
Caller: Execute external API call
โ
Scrubber: Overwrite key in memory with zeros
โ
Audit: Log to tamper-evident chain
๐ Security & Compliance
Pincer is built for enterprise-grade security:
- Hardware-Backed Cryptography: Master encryption keys never leave the OS-native keychain.
- Proxy Token Isolation: Agents only handle ephemeral
pxr_tokens; they never touch real credentials. - JIT Decryption: Secrets are decrypted only for the duration of the API call.
- Zero-Footprint Memory: Sensitive data is scrubbed (zeroed out) from memory immediately after use.
- Fine-Grained Authorization: Strict per-agent, per-tool access control policies.
- Tamper-Evident Audit Log: Append-only tool call history with SHA-256 chain-hashing.
- Hardened Execution: Schema validation on all inputs and protected environment execution.
- Stdio Compatible: Fully compatible with the standard Model Context Protocol transport.
๐ Audit Logs
Every tool call is logged to ~/.pincer/audit.jsonl with both UTC and Local timestamps, plus character counts and estimated token usage:
{
"agentId": "openclaw",
"tool": "gemini_generate",
"duration": 234,
"status": "success",
"input_chars": 156,
"output_chars": 423,
"estimated_input_tokens": 39,
"estimated_output_tokens": 106,
"timestamp_utc": "2026-02-05T08:32:00.000Z",
"timestamp_local": "2/5/2026, 2:02:45 PM",
"chainHash": "a1b2c3d4e5f6g7h8",
"prevHash": "0000000000000000"
}
Token Estimation: Pincer automatically estimates token usage using a 4:1 character-to-token ratio (~4 characters per token average). This provides consistent cost tracking across all AI providers without relying on provider-specific APIs.
Chain hashes provide tamper detection - any modification breaks the SHA-256 chain.
## ๐งช Development
```bash
# Install dependencies
npm install
# Run tests
npm test
# Run with watch mode
npm run dev
# Build for production
npm run build
๐ Documentation
- Setup Guide - Getting started with Pincer-MCP
- IDE Integration - Use Pincer with VSCode, Claude Desktop, Cursor, and more
- OpenClaw Integration - Integrate Pincer with OpenClaw agents
- Testing Guide - Comprehensive test suite documentation
- Capabilities Reference - Full API and feature documentation
- Security Policy - Vulnerability reporting and security best practices
- CHANGELOG - Version history and release notes
๐ค Contributing
Contributions are welcome! Please see CONTRIBUTING.md for guidelines.
๐ License
BSL 1.1 (Business Source License) โ See LICENSE for details. Converts to Apache 2.0 on 2028-04-01.
- Model Context Protocol - The standard for AI tool integration.
- keytar - Secure cross-platform keychain access.
- better-sqlite3 - High-performance local persistence.
Built with โค๏ธ for a more secure AI future.
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