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Speakeasy Platform MCP

Speakeasy Platform MCP

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speakeasy.comAI & Agents275Updated today

About Speakeasy Platform MCP

Speakeasy Platform MCP is an open-source control plane for organizations managing MCP servers, skills, and assistants. It combines access controls and threat inspection with usage and cost observability, plus centralized distribution to teams.

Key features

  1. 01Fine-grained access permissions
  2. 02Inspect prompts and agent actions
  3. 03Detect and handle sensitive data
  4. 04Track token usage and costs
  5. 05Centralized team distribution

Use cases

  1. 01Control access to team MCP servers
  2. 02Monitor AI usage and spending
  3. 03Enforce policies against sensitive data
  4. 04Distribute tools and assistants by role

MCP support

It provides a central control layer for connecting agents to MCP servers for SaaS vendors, APIs, and internal systems. MCPs, skills, and assistants can be centrally managed and distributed with permissions.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://ai.speakeasy.com/platform-mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Speakeasy

Speakeasy AI Control Plane

Securely scale AI usage across your organization. Built for humans and agents.
Learn more »

Documentation · Running locally · Tech Stack · Contributing · Login · Roadmap

Introduction

This repository is the open source stack behind Speakeasy's AI control plane. Secure and centrally manage MCPs, Skills, and Assistants your whole company to access, with fine-grained permissions, threat detection, and full observability of token use and costs. Every tool call, permission change, and access event logged and searchable. SOC 2 Type II and ISO 27001 certified.

To get started on the hosted platform you can Sign up, or check out the Quickstart guide.

Supports popular AI providers

Claude      Claude Code      ChatGPT      Codex      Gemini      Cursor      GitHub Copilot

Observe

Track AI usage across teams and measure impact with either tokens or cost. Deep dive expensive sessions, create budgets and measure tool effectiveness. Built on a foundation of Opentelemetry. Exportable and interactive via platform MCP and a built in assistant.

Secure

Every prompt, response, and agent action is inspected and enforced in real time. Sensitive data is blocked, redacted, or logged before it leaves your environment. Create and enforce flexible policies to prevent prompt injection, log shadow use and detect PII secrets and other sensitive data types.

Connect

A single control layer for connecting your agents to MCPs for your SaaS vendors, APIs, and internal systems, with policy enforcement and granular access control built in. Private networking and tunneling deployed on demand.

Distribute

Centralise distribution of MCPs, Skills, Plugins and Assistants to your team based on enterprise roles. Team, server, and tool level permissions enforced through RBAC and Oauth2.1. Synced to your enterprise IDP (Okta, Azure AD, Google Workspace, etc.).

Support

Running locally

Run ./zero until it succeeds. This script is what you use to run the dashboard and services for local development. It installs dependencies, runs pending database migrations, and starts everything up.

The main dependencies are Mise and Docker. The ./zero script will guide you to install these if they are not found.

Seed your local organization with a realistic working environment — a deployed API, agent sessions, telemetry, risk findings, teammates, and an API key:

mise seed

It talks to the databases directly, so it can run before the services are up, and re-running it resets the seeded data.

To work on several branches at once, each git worktree can run its own full stack on its own ports:

wt switch --create my-feature

See CONTRIBUTING.md for more detail on local development, auth, worktrees, and the CLI.

Contributing

Contributions are welcome! Please open an issue or discussion for questions or suggestions before starting significant work.

See CONTRIBUTING.md for development setup and detailed contribution guidelines.

Tech Stack

Contributors

Speakeasy contributors

Built by Speakeasy

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.