onemcp

One access point for AI agents to connect with tools and data

onemcp connects AI agents to external data sources, tools, and internal business systems. Instead of building separate integrations for each provider, teams use a single MCP endpoint. The agent specifies what it needs, and the platform finds the right source, handles the call, and charges the cost against a shared balance.

The platform works with Claude, Cursor, and custom MCP clients. It brings together MCP servers, APIs described with OpenAPI, undocumented APIs, and internal company APIs, making them accessible to agents through a unified interface.

How it works

The platform uses four meta-tools:

  • search - discover relevant data sources and tools.
  • describe - retrieve information about a selected service and how to use it.
  • call - execute tool and API calls.
  • balance - check the available balance.

This gives agents four entry points instead of requiring them to keep hundreds of integration schemas in context. The platform also centralizes access policies, usage limits, and call auditing.

Key capabilities

  • Unified access to multiple sources - tools and data available through a single MCP endpoint.
  • Integration with business systems - connectivity to internal APIs and external services.
  • Centralized billing - access to paid APIs through a single balance, with support for your own API keys.
  • Usage control - access policies, allowlists, limits, and audit trails.
  • Enterprise deployment options - EU data hosting and on-premises deployment.

Who it is for

onemcp is designed for startups, AI developers, and fintech companies looking to simplify integrations and data access. It supports use cases across finance, banking, crypto, Web3, and automation. Banks can use its access controls and auditing capabilities, while integrators and data providers can deliver deployments and make their own APIs available in the catalog.

See onemcp in action

Discover how an AI agent finds sources, uses tools, and retrieves data through a single interface during a 20-minute demo using live data sources.