| name | apideck-mcp |
| description | Front-door skill for the Apideck MCP server — 330 unified-API tools across 10 domains plus 4 intent-grouped workflow tools, exposed via dynamic discovery. Use when the user is building an MCP-based agent (Claude Code, OpenAI Agents SDK, Pydantic AI, LangChain) and wants to integrate with any of the 200+ SaaS connectors Apideck covers. Hosted at mcp.apideck.dev/mcp; stdio transport via `npx -y @apideck/mcp` for local development. |
| license | Apache-2.0 |
| alwaysApply | false |
| metadata | {"author":"apideck","version":"1.0.0"} |
Apideck MCP
The Apideck MCP server exposes the Unified API as Model Context Protocol tools. One MCP server, 330+ tools, 200+ SaaS connectors.
If you're building an agent that needs to read/write SaaS data — invoices, candidates, employees, files, tickets, customers — and your agent runtime supports MCP (Claude Code, Claude Desktop, Cursor, Windsurf, OpenAI Agents SDK, Pydantic AI, LangChain), this is usually the right choice over a language SDK.
When to prefer MCP over the language SDK
| Use the MCP server when… | Use a language SDK (apideck-node, apideck-python, …) when… |
|---|
| You're building an agent (LLM-driven control flow) | You're building a deterministic backend integration |
| You want dynamic tool discovery — agent picks tools at runtime | You know at compile time which methods you'll call |
| Your runtime already speaks MCP (Claude Code, Cursor, OpenAI Agents SDK, …) | You're embedding Apideck inside a non-agent service |
| You want Vault OAuth elicitation handled for free (consent URLs surface as MCP elicitations) | You'll wire OAuth flows yourself |
| Tool descriptions matter for agent decision-making | Your code knows which method to call regardless of description quality |
Endpoints
Hosted: https://mcp.apideck.dev/mcp
Stdio: npx -y @apideck/mcp
Source: https://github.com/apideck-libraries/mcp
Pass credentials via headers (HTTP)
x-apideck-api-key: <your Apideck API key>
x-apideck-app-id: <your application ID>
x-apideck-consumer-id: <end-user / customer ID>
Pass credentials via env vars (stdio)
APIDECK_API_KEY=... APIDECK_APP_ID=... APIDECK_CONSUMER_ID=... npx -y @apideck/mcp
IMPORTANT RULES
- PREFER dynamic mode (
?mode=dynamic or --dynamic, the default). It exposes 4 meta-tools — list_tools, describe_tool_input, execute_tool, list_scopes — instead of 330 individual tools, dropping initial token cost from ~25-40K to ~1,300. Switch to static mode only for small fixed tool sets.
- CALL
list_tools first with relevant search_terms (["accounting", "invoices"], ["hris", "employees"]). Don't enumerate 330 tools.
- PREFER workflow tools over manual chains — see "Intent-grouped workflows" below. The agent that picks
apideck-pay-bill instead of stitching accounting-bills-get + accounting-bill-payments-create will succeed more often and leak less context.
- HANDLE URL elicitations: when an upstream call hits a missing/expired Vault connection, the server throws
UrlElicitationRequiredError (MCP error code -32042) carrying a one-time consent URL. Surface this URL to the user, wait for them to complete OAuth, then retry the original tool call.
- USE
x-apideck-service-id when a consumer has multiple connections of the same unified API — e.g. the consumer connected both Xero and QuickBooks, and the user wants the call to target Xero. Without this, Apideck routes to whichever connection is first.
- USE scopes to restrict an agent to a subset of capabilities —
?scopes=read for analysis agents, ?scopes=read,write to allow non-destructive changes, omit for full access. Scopes are enforced server-side, so a "read-only" agent literally cannot call destructive tools no matter what the prompt says.
Intent-grouped workflows
The MCP server ships 4 high-level workflow tools alongside the 330 endpoint tools. Each workflow orchestrates 2-4 underlying calls behind a single intent. Prefer these when they match the user's task — agents picking the right workflow succeed more often than agents stitching the chain manually.
Workflows return a structured result with failingStep so you know which leg of the chain broke when something fails. Partial successes (e.g. one report unsupported by the connector) come back as useful data, not opaque errors.
Mode selection
The server supports three operational modes:
- Dynamic mode (default): 4 meta-tools, ~1,300 initial tokens, agent discovers via
list_tools. Use this.
- Static mode: All 330+ tools listed up front, ~25-40K tokens. Use only when you're filtering to a tiny subset (e.g.
?include=accounting-invoices-list,accounting-invoices-get) and want the schemas resolved at handshake.
- Code mode (
?mode=code, experimental): Agent writes JavaScript against an apideck.* SDK in a sandbox. Beta — currently uses vm.createContext which isn't production-hardened. Skip for production agents.
Coverage
330 tools across these unified APIs:
| API | Tools | Examples |
|---|
| Accounting | 143 | invoices, bills, payments, suppliers, customers, P&L, balance sheet, journal entries |
| CRM | 50 | companies, contacts, leads, opportunities, pipelines, activities |
| File Storage | 32 | files, folders, drives, shared links, upload sessions |
| HRIS | 25 | employees, departments, payrolls, time-off requests |
| Vault | 23 | connections, consumers, sessions, custom mappings, logs |
| ATS | 15 | applicants, applications, jobs |
| Issue Tracking | 15 | tickets, comments, users, tags |
| Connector | 8 | API discovery, coverage metadata |
| Ecommerce | 7 | customers, orders, products, stores |
| Webhook | 6 | webhook subscriptions, logs |
| Proxy | 6 | direct GET/POST/PUT/PATCH/DELETE for connector-native endpoints not yet in the unified spec |
Worked example: list invoices in dynamic mode
Agent: list_tools(search_terms: ["accounting", "invoices"])
→ Returns: [
"accounting-invoices-list",
"accounting-invoices-get",
"accounting-invoices-create",
"accounting-invoices-update",
"accounting-invoices-delete"
]
Agent: describe_tool_input(tool_name: "accounting-invoices-list")
→ Returns: {
filter: { updated_since, status, ... },
cursor: string,
limit: number,
"x-apideck-service-id": string,
...
}
Agent: execute_tool(
tool_name: "accounting-invoices-list",
input: { limit: 10, "x-apideck-service-id": "quickbooks" }
)
→ Returns: { data: [...], meta: { cursors: { next: "..." } } }
Initial cost: ~1,300 tokens for the meta-tools. The agent fetches schemas only for tools it intends to call.
Related skills
Reference
