Apideck MCP Server

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

Recommended — prebuilt bundle:

Drag and drop the prebuilt mcp-server.mcpb onto Claude Desktop. Claude reads manifest.json to prompt for credentials and spawn the server — no manual config needed.

[!NOTE] Learn more about Desktop Extensions.

Local stdio (npx) alternative:

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "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"
      }
    }
  }
}

Restart Claude Desktop after saving. Pin a specific version by replacing @apideck/mcp with @apideck/[email protected].

Set credentials in your shell:

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

Hosted (recommended):

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"

Local stdio (npx):

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

The start command reads credentials from environment variables only — it does not accept --api-key / --consumer-id / --app-id flags.

Settings → Cascade → Manage MCPs → View raw config, then paste:

{
  "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:

| API | Tools | Coverage | |---|---|---| | Accounting | 143 | Invoices, bills, payments, suppliers, customers, journal entries, ledger accounts, purchase orders, tax rates, P&L, balance sheet, and more | | CRM | 50 | Companies, contacts, leads, opportunities, pipelines, notes, activities, users | | File Storage | 32 | Files, folders, drives, shared links, upload sessions | | HRIS | 25 | Employees, companies, departments, payrolls, time-off requests | | Vault | 23 | Connections, consumers, sessions, custom mappings, logs | | ATS | 15 | Applicants, applications, jobs | | Issue Tracking | 15 | Collections, tickets, users, tags, comments | | Connector | 8 | APIs, connectors, resources, coverage metadata | | Ecommerce | 7 | Customers, orders, products, stores | | Webhook | 6 | Webhook subscriptions, logs | | Proxy | 6 | GET, POST, PUT, PATCH, DELETE, OPTIONS |

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.

| Tool | What it does | Calls | |---|---|---| | apideck-month-end-close-check | Fans out aged-creditors, aged-debtors, balance-sheet, and P&L in parallel. Returns a partial result when some reports aren't supported by the connector. | 4 |

Hosted

The server is live at:

https://mcp.apideck.dev/mcp

Pass credentials via headers:

| Header | Description | |---|---| | x-apideck-api-key | Your Apideck API key | | x-apideck-consumer-id | The end-user / customer ID in your app | | x-apideck-app-id | Your Apideck application ID |

Three Modes

| Mode | Tools exposed | Initial tokens | Best for | |---|---|---|---| | dynamic (default) | 4 meta-tools | ~1,300 | General-purpose agents, token-sensitive contexts | | static | All 330 tools | ~35–55K | Focused agents doing a specific API | | code | apideck_search + apideck_run | ~600 | Agents that call endpoints programmatically via JS |

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:

| Scope | HTTP methods | Flag | |---|---|---| | read | GET, HEAD | --scope read | | write | POST, PUT, PATCH | --scope write | | destructive | DELETE | --scope destructive |

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.

Contributing

See CONTRIBUTING.md for local setup, dev workflow, commit conventions, and the release process.

Regenerating src/tools.ts

src/tools.ts is generated from the Apideck OpenAPI spec via the generate-and-pr workflow.

Trigger via GitHub Actions

1. Set the APIDECK_SPEC_URL repo variable once (Settings → Secrets and variables → Actions → Variables).
2. Go to Actions → generate-and-pr → Run workflow.
3. The workflow runs pnpm generate + pnpm parity-probe, commits src/tools.ts and reports/*.json on a bot/spec-update-<run_id> branch, and opens a PR with the tool-count delta and parity summary.

Note: Bot PRs opened via GITHUB_TOKEN do not auto-trigger CI. Re-run manually from the Actions tab, or push an empty commit from a maintainer branch.

Regenerate locally

# 1. Generate src/tools.ts from spec
pnpm generate

# 2. Check tool-count parity against the reference
pnpm parity-probe

# 3. Build
pnpm build

# 4. Run tests
pnpm test

Parity reports are written to reports/ and uploaded as the parity-reports artifact on each workflow run.

License

MIT