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Securely scale AI usage across your organization. Built for humans and agents.
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Speakeasy Control Plane helps your organization connect, secure, and manage MCPs, Skills, and Assistants. It provides fine-grained permissions, threat detection, and visibility into token use and costs. Tool calls, permission changes, and access events are logged and searchable. The platform is SOC 2 Type II and ISO 27001 certified.
Naming note: The product is now called Speakeasy Control Plane. It was previously called Gram, and this GitHub repository has not yet been renamed (speakeasy-api/gram).
To get started on the hosted platform, sign up or read the getting started guide.
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.
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.
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.
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.).
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.
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.