Eventually I came down to this solution: - It uses in-memory semantic search to find relevant Api endpoints by natural language (such as list
Any Openapi MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Eventually I came down to this solution: - It uses in-memory semantic search to find relevant Api endpoints by natural language (such as list products) - It returns the complete end-point docs (as I designed it to store one endpoint as one.
The server ships on npm as @smithery/cli, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
You will need 2 environment variables: OPENAPI_JSON_DOCS_URL, API_REQUEST_BASE_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Plenty of knowledge and memory servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. It is maintained by baryhuang; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
{
"mcpServers": {
"server-any-openapi": {
"command": "npx",
"args": ["-y", "@smithery/cli"],
"env": {
"OPENAPI_JSON_DOCS_URL": "your-value",
"API_REQUEST_BASE_URL": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| OPENAPI_JSON_DOCS_URL | Endpoint or connection string the server talks to. | Yes |
| API_REQUEST_BASE_URL | Endpoint or connection string the server talks to. | Yes |
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.