Pincer

io.github.VouchlyAIPublished by GitHub account VouchlyAIv0.1.5Updated Oct 24, 2026

Secure grip for your agent's secrets - security-hardened MCP gateway with proxy token architecture

Overview

AI-generated overview

A local MCP gateway that lets an assistant call LLM providers and sign or decrypt data using proxy tokens instead of real API keys.

What you can do
Pincer runs as a local stdio MCP server that brokers calls to external services on the agent's behalf. Tools include gemini_generate, openai_chat, openai_list_models, openai_compatible_chat, openai_compatible_list_models, claude_chat, openrouter_chat, openrouter_list_models, openwebui_chat, openwebui_list_models, gpg_sign_data and gpg_decrypt. The agent authenticates with a proxy token; Pincer resolves it to the real credential stored encrypted in the OS keychain, injects it just in time, and logs each call to a hash-chained audit file.
When to use it
Use it when an assistant needs to reach several LLM providers or perform GPG signing without holding long-lived API keys or private keys itself. It suits setups where per-agent, per-tool authorization and an audit trail of tool calls matter.
Requirements
Node.js 18+ and an OS with native keychain support (macOS, Windows, or Linux). Install the npm package pincer-mcp, run pincer init to create the vault, store provider keys, and register an agent to obtain a proxy token. The agent must be given PINCER_PROXY_TOKEN; optional variables are AUDIT_LOG_PATH, OPENAI_COMPATIBLE_URL and OPENWEBUI_URL. Network access is needed for the external provider calls.
Before you install
The vault holds real provider API keys and GPG private keys, so the machine and the OS keychain account are the trust boundary. PINCER_PROXY_TOKEN is a bearer credential: anyone holding it can invoke the tools that agent is authorized for. gpg_sign_data and gpg_decrypt act on data supplied by the agent, and every tool call is written to the audit log at ~/.pincer/audit.jsonl. Prompts and payloads are forwarded to the selected third-party providers.

Installation

In SourceWeft

  1. Open Pincer in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Pincer MCP 🦀

[Pincer-MCP]

[License] [TypeScript] [MCP] [NPM Version] [NPM Downloads] [MCP Registry]

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.

🔒 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

✨ The Solution: Proxy Token Architecture

Pincer implements a "blindfold" security model:

  1. Agent knows: Only a unique proxy token (pxr_abc123...)
  2. Pincer knows: Mapping of proxy tokens → real API keys (encrypted in OS keychain)
  3. Agent never sees: The actual credentials
mermaid
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)

📦 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 — agent never sees the key)
  • gpg_decrypt: Decrypt PGP-encrypted data using a vault-stored private key.

🔑 GPG Key Management

bash
# Generate a new GPG keypair (private key stored in vault)pincer key generate --name "Release Signing" --email [email protected]
# Import an existing PGP private keypincer key import ./my-key.asc --passphrase "my-passphrase"
# List all stored GPG keyspincer key list
# Export public key (safe to share)pincer key export <key-id>
# Authorize an agent for signingpincer agent authorize mybot gpg_sign_data --key <key-id>

(More callers coming soon!)

🚀 Quick Start

Prerequisites

  • Node.js 18+
  • macOS, Windows, or Linux with native keychain support

Installation

Option 1: Global Installation (Recommended)

bash
npm install -g pincer-mcp# Now 'pincer' command is available system-wide

Option 2: Local Development

bash
git clone https://github.com/VouchlyAI/Pincer-MCP.gitcd Pincer-MCPnpm installnpm run buildnpm link  # Makes 'pincer' command available locally

Setup Vault

bash
# 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 tokenpincer agent add openclaw# Output: 🎫 Proxy Token: pxr_V1StGXR8_Z5jdHi6B-myT
# 4. Authorize the agent for specific toolspincer agent authorize openclaw gemini_generate

Multi-Key Support

Store multiple keys for the same tool and assign them to different agents:

bash
# Store two different Gemini API keyspincer set gemini_api_key "AIzaSy_KEY_FOR_CLAWDBOT..." --label key1pincer set gemini_api_key "AIzaSy_KEY_FOR_MYBOT..." --label key2
# View all stored keyspincer list
# Assign specific keys to each agentpincer agent add clawdbotpincer agent authorize clawdbot gemini_generate --key key1
pincer agent add mybot  pincer agent authorize mybot gemini_generate --key key2
# View agent permissionspincer agent list

Result: clawdbot uses key1, mybot uses key2 - perfect for rate limiting or cost tracking!

Run the Server

bash
npm run dev

Configure Your Agent

Give your agent the proxy token (not the real API key):

bash
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:

json
{  "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.

🏗️ 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 → Agent ID mappings
    • agent_mappings: Agent ID → Tool authorization

Authentication Flow

Request (_meta.pincer_token: pxr_xxx)  ↓Gatekeeper: Extract proxy token from body  ↓Vault: Resolve pxr_xxx → agent_id → tool_name → real_api_key  ↓Injector: JIT decrypt & inject real key  ↓Caller: Execute external API call  ↓Scrubber: Overwrite key in memory with zeros  ↓Audit: Log to tamper-evident chain

🔐 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.

🔍 Audit Logs

Every tool call is logged to ~/.pincer/audit.jsonl with both UTC and Local timestamps, plus character counts and estimated token usage:

json
{  "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.
## 🧪 Development
```bash# Install dependenciesnpm install
# Run testsnpm test
# Run with watch modenpm run dev
# Build for productionnpm run build

📚 Documentation

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

📄 License

BSL 1.1 (Business Source License) — See LICENSE for details. Converts to Apache 2.0 on 2028-04-01.


Built with ❤️ for a more secure AI future.

Source: README.md at commit 5ca44e7

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.1.5LatestSep 16, 2026

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