How to Use the Apiary MCP in LangChain

Q: Does this Apiary MCP Server support LangSmith tracing in LangChain?

Absolutely. Every tool execution like getapi or listapis appears as a distinct step in your LangSmith dashboard with full latency metrics.

Chain Apiary design steps with LangChain to pull blueprints, run Dredd tests, and publish docs in a single observable agent run.

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Connect Apiary MCP to LangChain

Create your Vinkius account to connect Apiary to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Apiary with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automate API deployments inside LangChain chains

Your agent fetches blueprint source code using `get_api` and updates designs with `publish_blueprint` inside a single LangChain run. This setup eliminates manual copy-pasting when your API design shifts. We route these tool calls through our Vinkius MCP Server setup, ensuring your agent fetches live markdown documentation and mock URLs via `get_doc_url` on the fly. You get a complete, traceable run history inside LangSmith to debug schema mismatches instantly.

Run automated Dredd test suites on demand

This integration runs `run_tests` to execute Dredd-style validation against your live mock servers inside your LangChain pipeline. Stop wondering if your implementation actually matches your design docs. By feeding the test results directly into your LLM chain, the agent writes fixes for broken endpoints. The API blueprint stays updated because the agent handles the heavy lifting without leaving your development environment.

Manage team workspaces during agent execution

Your LangChain agent queries `list_teams` and `list_team_apis` to discover project structures automatically before generating new endpoints. Large teams often struggle to keep API projects synced across different departments. If a new developer joins, the agent checks access using `list_team_members` to verify permissions. Having this MCP capability inside your chain prevents unauthorized blueprint modifications.

Setup guide

Set up Apiary MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Apiary tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "apiary-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Apiary transactions"
    })
    print(result["messages"][-1].content)

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Why Choose Vinkius

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Common questions about Apiary MCP in LangChain

You configure your token once in the Vinkius dashboard. The MultiServerMCPClient securely injects the credentials, so your LangChain code never exposes your raw API keys.

Yes, that is exactly how you should use this. Your agent gets test failures from `run_tests`, modifies the blueprint, and updates Apiary with `publish_blueprint`.

Absolutely. Every tool execution like `get_api` or `list_apis` appears as a distinct step in your LangSmith dashboard with full latency metrics.

You instantiate the MultiServerMCPClient pointing to our hosted MCP endpoint. This aggregates the Apiary tools with other servers in your pipeline.

Your API blueprints and team rosters process in ephemeral V8 sandboxes. We never write your design files or credentials to persistent disks.

Use it with your favorite AI tools

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