mcp

npm version MCP Registry Glama score voke MTQS License: MIT

Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent to 200+ connectors — accounting systems, HRIS platforms, CRM, file storage, and more — through one integration.

Quick Connect

Install in Cursor Install in VS Code

{
  "mcpServers": {
    "apideck": {
      "command": "npx",
      "args": ["-y", "@apideck/mcp", "start"],
      "env": {
        "APIDECK_API_KEY": "YOUR_API_KEY",
        "APIDECK_CONSUMER_ID": "YOUR_CONSUMER_ID",
        "APIDECK_APP_ID": "YOUR_APP_ID"
      }
    }
  }
}

export APIDECK_API_KEY="..."
export APIDECK_CONSUMER_ID="..."
export APIDECK_APP_ID="..."

claude mcp add --transport http apideck https://mcp.apideck.dev/mcp \
  --header "Authorization: Bearer $APIDECK_API_KEY" \
  --header "x-apideck-consumer-id: $APIDECK_CONSUMER_ID" \
  --header "x-apideck-app-id: $APIDECK_APP_ID"

claude mcp add apideck \
  -e APIDECK_API_KEY="$APIDECK_API_KEY" \
  -e APIDECK_CONSUMER_ID="$APIDECK_CONSUMER_ID" \
  -e APIDECK_APP_ID="$APIDECK_APP_ID" \
  -- npx -y @apideck/mcp start

{
  "mcpServers": {
    "apideck": {
      "url": "https://mcp.apideck.dev/mcp",
      "headers": {
        "x-apideck-api-key": "YOUR_API_KEY",
        "x-apideck-consumer-id": "YOUR_CONSUMER_ID",
        "x-apideck-app-id": "YOUR_APP_ID"
      }
    }
  }
}

{
  "mcpServers": {
    "apideck": {
      "url": "https://mcp.apideck.dev/mcp",
      "headers": {
        "x-apideck-api-key": "YOUR_API_KEY",
        "x-apideck-consumer-id": "YOUR_CONSUMER_ID",
        "x-apideck-app-id": "YOUR_APP_ID"
      }
    }
  }
}

Claude Desktop (.mcpb plugin bundle)

Apideck ships a Claude plugin bundle (.mcpb — Anthropic's Model Context Protocol Bundle format). Drop it into Claude Desktop and you get the full server (330 endpoint tools + 4 workflow tools) with API key / consumer ID / app ID prompted via the standard plugin UI.

pnpm mcpb:build       # → dist/mcp-server.mcpb (~590 KB)

The bundle is built locally; CI publication to GitHub Releases is deferred. Open the .mcpb with Claude Desktop's plugin installer; Claude Desktop reads manifest.json to wire credentials and spawn the server.

Tools

330 tools across 10 unified APIs:

Workflow tools

Intent-grouped workflows orchestrate multiple calls behind a single MCP tool — saving agents the round-trips and field-plumbing they routinely get wrong.

Hosted

The server is live at:

https://mcp.apideck.dev/mcp

Pass credentials via headers:

Three Modes

Dynamic mode

Agents discover tools progressively — ~85% fewer tokens than loading all 330 schemas upfront:

list_tools({})
  → { total: 330, domains: [{ name: "accounting", count: 143 }, ...],
      hint: "Call list_tools(domain=X) or list_tools(search_terms=[...])" }

list_tools({"search_terms": ["invoices"]})
  → accounting-invoices-list, accounting-invoices-create, accounting-invoices-get, ...

describe_tool_input({"name": "accounting-invoices-list"})
  → Full JSON Schema with all parameters

execute_tool({"name": "accounting-invoices-list", "input": {"request": {"limit": 10}}})
  → Invoice data from the connected accounting system

You can combine dynamic mode with a scope filter:

{
  "mcpServers": {
    "apideck": {
      "command": "node",
      "args": ["dist/bin/mcp.js", "--mode", "dynamic", "--scope", "read"],
      "env": { "APIDECK_API_KEY": "...", "APIDECK_CONSUMER_ID": "...", "APIDECK_APP_ID": "..." }
    }
  }
}

Code mode

Code mode exposes two tools instead of 330+. Designed for agents that prefer calling endpoints as methods rather than tool calls:

1. apideck_search — find endpoints by substring, returns camelCase method names
2. apideck_run — execute a JS script with apideck.<methodName> bound to live endpoint dispatchers, sandboxed in node:vm

apideck_search("invoices")
  → {
      count: 4,
      endpoints: [
        { name: "accounting-invoices-list",   method: "accountingInvoicesList" },
        { name: "accounting-invoices-create",  method: "accountingInvoicesCreate" },
        { name: "accounting-invoices-get",     method: "accountingInvoicesGet" },
        { name: "accounting-invoices-delete",  method: "accountingInvoicesDelete" }
      ]
    }

apideck_run({
  script: "return await apideck.accountingInvoicesList({ request: { limit: 5 } })"
})
  → Invoice data from the connected accounting system

The sandbox strips process, require, fs, child_process, and other Node globals — scripts only have access to the apideck object.

Scopes

Filter tools by HTTP method class:

Connect from Any Agent Framework

Remote (hosted — no local install)

# OpenAI Agents SDK
from agents import Agent
from agents.mcp import MCPServerHTTP

agent = Agent(
    name="Apideck Agent",
    mcp_servers=[MCPServerHTTP(
        url="https://mcp.apideck.dev/mcp",
        headers={
            "x-apideck-api-key": "...",
            "x-apideck-consumer-id": "...",
            "x-apideck-app-id": "..."
        }
    )]
)

# Pydantic AI
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

agent = Agent("anthropic:claude-sonnet-4-5", mcp_servers=[
    MCPServerHTTP(
        url="https://mcp.apideck.dev/mcp",
        headers={
            "x-apideck-api-key": "...",
            "x-apideck-consumer-id": "...",
            "x-apideck-app-id": "..."
        }
    )
])

# LangChain / LangGraph
from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
    "apideck": {
        "url": "https://mcp.apideck.dev/mcp",
        "transport": "streamable_http",
        "headers": {
            "x-apideck-api-key": "...",
            "x-apideck-consumer-id": "...",
            "x-apideck-app-id": "..."
        }
    }
})
tools = await client.get_tools()

Local stdio (for development)

pnpm install
pnpm build

# Dynamic mode (default)
APIDECK_API_KEY=... APIDECK_CONSUMER_ID=... APIDECK_APP_ID=... node dist/bin/mcp.js start

# Static mode (all 330 tools)
APIDECK_API_KEY=... node dist/bin/mcp.js start --mode static

# Code mode
APIDECK_API_KEY=... node dist/bin/mcp.js start --mode code

# Read-only
APIDECK_API_KEY=... node dist/bin/mcp.js start --scope read

# OpenAI Agents SDK (local stdio)
from agents import Agent
from agents.mcp import MCPServerStdio

mcp = MCPServerStdio(name="apideck", params={
    "command": "node",
    "args": ["dist/bin/mcp.js", "start", "--mode", "dynamic"],
    "env": {
        "APIDECK_API_KEY": "...",
        "APIDECK_CONSUMER_ID": "...",
        "APIDECK_APP_ID": "..."
    }
})
agent = Agent(name="Apideck Agent", mcp_servers=[mcp])

Reliability

The runtime automatically retries failed requests so transient errors don't surface to your agent:

• Retried status codes: 408, 500, 502, 503, 504
• Retried network errors: ECONNRESET, ECONNREFUSED, ETIMEDOUT, and similar
• Strategy: exponential backoff, up to 4 attempts, capped at 30 s
• Idempotency: retries only fire on GET, HEAD, PUT, DELETE, OPTIONS, TRACE — POST/PATCH are not retried automatically

Binary Content

File Storage endpoints that return images or audio send them as native MCP content blocks rather than base64 strings in JSON:

{ "type": "image", "data": "<base64>", "mimeType": "image/png" }
{ "type": "audio", "data": "<base64>", "mimeType": "audio/mpeg" }

Agents that support multi-modal MCP content (Claude, GPT-4o) receive the raw bytes — no extra decoding step needed.

License

MIT