Apideck MCP Server - Give AI agents access to real-time data across 200+ apps
Don't let Claude and Codex roam free on your customers' SaaS data.
Apideck MCP gives AI agents permissioned access to 200+ apps, including Accounting, CRM, HRIS, ATS, and more, through a single endpoint.
Scoped read/write permissions and field-level redaction are enforced at the MCP layer.
Works with any MCP client (Claude, Cursor, Codex, Windsurf, LangChain, Vercel AI SDK) and agent runtimes like OpenClaw and Hermes.
One MCP server. 200+ apps. Production-ready.
Replies
Really like this direction. Tool access for agents sounds simple until you’re juggling huge tool surfaces, token limits and permissions. The dynamic discovery part is clever. Wonder how performance looks when workflows get long and agents keep discovering more tools on the go.
apideck
@jaidevxb you can already limit what permissions your MCP will have in the Apideck's dashboard.
We only recently solved this problem in an Italian financial project. It’s a pity I didn’t know about you back then - we spent a lot of time on this stage.
apideck
@natalia_iankovych Ahh, if we had launched earlier, maybe you could have used it. But now you do.
How did you approach it? And how did you solve this problem?
@srbhr We integrated all the required APIs one by one. There were many of them, and we had a lot of issues with some government agency APIs, but overall this is a typical task for us.
200+ app integrations through one clean protocol for agents is super useful. Been thinking about this problem for a side project and doing it manually is a pain. Does it support custom endpoints or just the 200 built-in ones?
The token optimization here is genuinely clever. Most MCP servers just dump 200+ tools at startup and burn 40K tokens before an agent does anything useful. Reducing that to 4 meta-tools with on-demand discovery feels like the difference between a production-ready agent and a demo toy. One question: how are you handling rate limits during dynamic discovery - does each discovery call count against integration/API quotas, or is there some caching layer involved?
apideck
@sathvika_yadav03 Thanks! Yeah, that was the whole point, we wanted discovery to be essentially free. The tool inventory is generated at build time from our OpenAPI spec and lives in memory, so list_tools and describe_tool_input never touch the network. You can call them as many times as you want with zero API quota impact. Only execute_tool hits our API, and those calls count against your normal rate limits like any direct REST call would. No caching layer in between, just a static inventory plus lazy JSON-schema emission when the agent actually asks for it.
MCP as connective tissue for agents is still underrated. What Apideck does here — normalized, pre-built access to 200+ apps without custom integration per tool — is exactly the boring-but-critical infrastructure that makes the rest of the agent stack actually work in production. My question is around multi-tenant setups: if I'm building an agent that operates on behalf of different users, does Apideck handle per-user auth token isolation, or does that fall on the developer?
Permissioned access is the key piece most MCP servers are missing right now. Everyone's building MCP integrations but nobody's thinking about what happens when an AI agent has unrestricted write access to a customer's CRM. The field-level redaction layer is smart - how granular can you get with the permission scoping?