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MCP API Connect

by bvenkataversion 0.1.0i★ –iRuns on your computer
Registry nameio.github.bvenkata/mcp-api-connect

Install

Overview

Description from the maker (original English)

Protocol- & auth-agnostic API connector: SOAP/REST behind any auth, config-driven. Lib/API/MCP.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "api-connect": {
      "command": "uvx",
      "args": [
        "mcp-api-connect"
      ]
    }
  }
}

Run this in your terminal

claude mcp add api-connect -- uvx mcp-api-connect

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "api-connect": {
      "command": "uvx",
      "args": [
        "mcp-api-connect"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "api-connect": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-api-connect"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account bvenkata, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32661 servers in this category
  • Published to the registry more recently than 30% of the other 32661 servers in this category
  • Basic checks equal to or better than 100% of the other 32661 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP API Connect safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Claude Checkpoint MCP

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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Claude Checkpoint MCP

by daniel-munoz

MCP server that checkpoints Claude Code session context to survive crashes and token limits

Runs on your computerUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

mcp-api-connect™

One payload in, any API out. mcp-api-connect is a protocol- and auth-agnostic connector engine: describe a target service (URL, protocol, auth, request/ response shape) once, then send it a normalized payload and get a normalized response back — whether the target is a REST/JSON API, a legacy SOAP service, protected by an API key, Basic auth, a Bearer token, or OAuth2 client credentials.

It ships as three things built on the same core engine, so however you want to use it, you can:

  • A Python library — pip install mcp-api-connect, call MCPAPIConnectEngine directly, no server required.
  • A standalone HTTP API — pip install mcp-api-connect[api], run mcp-api-connect-api, POST to /invoke.
  • An MCP server — pip install mcp-api-connect[mcp], run mcp-api-connect, point any MCP client (Claude, etc.) at it so an agent can call registered connectors — or arbitrary services on the fly — as tools.

Why

Every integration project reinvents the same wheel: a REST client here, a SOAP client there, one auth flow per service, ad-hoc request/response mapping scattered across the codebase. mcp-api-connect centralizes that into one declarative spec (InvokeSpec) and one execution engine, so adding a new target service is config, not code.

Quick start (library)

pip install mcp-api-connect
import asyncio

from mcp_api_connect import MCPAPIConnectEngine, InvokeSpec, Target, AuthSpec, AuthType, RequestFormat, ResponseFormat

spec = InvokeSpec( target=Target(base_url="https://api.example.com"), auth=AuthSpec(type=AuthType.API_KEY, config={"api_key": "secret", "header_name": "X-API-Key"}), request_format=RequestFormat(method="POST", path="/v1/orders", content_type="json"), response_format=ResponseFormat(content_type="json"), )

async def main(): async with MCPAPIConnectEngine() as engine: result = await engine.invoke(spec, {"customer": "jane"}) print(result.success, result.data)

asyncio.run(main())

Quick start (HTTP API)

pip install "mcp-api-connect[api]"

mcp-api-connect-api # serves on :8000, interactive docs at /docs

curl -X POST http://localhost:8000/invoke -H 'content-type: application/json' -d '{

"spec": { "target": {"base_url": "https://api.example.com"}, "auth": {"type": "api_key", "config": {"api_key": "secret"}}, "request_format": {"method": "POST", "path": "/v1/orders"}, "response_format": {"content_type": "json"} }, "payload": {"customer": "jane"} }'

Register a reusable connector once, then invoke it by name:

curl -X POST http://localhost:8000/connectors -d '{"name": "orders-api", "spec": {...}}'

curl -X POST http://localhost:8000/connectors/orders-api/invoke -d '{"customer": "jane"}'

Quick start (MCP)

pip install "mcp-api-connect[mcp]"
{

"mcpServers": { "mcp-api-connect": { "command": "/path/to/.venv/bin/mcp-api-connect" } } }

Or run it in a container (stdio transport):

docker build -t mcp-api-connect .

docker run --rm -i mcp-api-connect

Exposes tools: invoke (stateless, one-off), register_connector, list_connectors, invoke_connector (by name), delete_connector. An agent can register a connector for "the Salesforce API" once, then just say "call it with this payload" from then on.

➜ Full setup for Claude Desktop / Claude Code / Cursor, persistence, security notes, and a worked example: [docs/mcp-integration.md](docs/mcp-integration.md).

Core concepts

  • `Target` — base URL, protocol (rest | soap), timeout, default headers.
  • `AuthSpec` — type (none, api_key, basic, bearer, oauth2_client_credentials) + a config dict shaped for that type. OAuth2 tokens are fetched and cached automatically.
  • `RequestFormat` / `ResponseFormat` — content type (json, xml, soap) plus a declarative field_map ({"target.path": "$.source.jsonpath"}) for reshaping payloads without writing code, or a Jinja2 body_template for full control (required for SOAP envelopes).
  • `InvokeSpec` — bundles the three above; the unit of "how to reach one service." Store it as a named Connector or pass it inline per call.

See src/mcp_api_connect/core/models.py for the full schema, and docs/auth-reference.md for the config shape each auth type expects.

Documentation

  • docs/mcp-integration.md — full MCP client setup (Claude Desktop, Claude Code, Cursor), persistence, security, tool reference, worked example, troubleshooting
  • docs/auth-reference.md — config fields for every auth type
  • CONTRIBUTING.md — dev setup, running tests, PR expectations

Extending

  • New auth type: implement AuthStrategy, register via engine.register_auth_strategy(...).
  • New protocol (e.g. GraphQL): implement ProtocolAdapter, register via engine.register_adapter(...).
  • New connector storage backend: implement ConnectorStore (ships with InMemoryConnectorStore and SqliteConnectorStore, credentials encrypted at rest via Fernet).

Roadmap

  • OAuth2 authorization-code flow, mTLS, AWS SigV4 auth strategies
  • WSDL-driven SOAP (optional zeep-backed adapter, no hand-written envelope needed)
  • GraphQL adapter
  • Postgres-backed ConnectorStore
  • Retry/backoff + rate limiting policies per connector
  • SSRF-safe target allow-listing for public deployments

Development

python -m venv .venv && source .venv/bin/activate

pip install -e ".[dev,api,storage,mcp]" pytest

License

Apache License 2.0 — see LICENSE and NOTICE.

Contributions are accepted under the same license (inbound = outbound); see CONTRIBUTING.md.

Trademark

mcp-api-connect™ is a trademark of Balaji Venkatasubramaniyar. The Apache 2.0 license covers copyright and patents but grants no trademark rights. You may use the name to refer to this project and to state compatibility, but not to name a fork, product, or service, or to imply endorsement. See TRADEMARKS.md for the full policy.

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