How to Use the Felt (Collaborative Maps) MCP in LangChain

Chain Felt (Collaborative Maps) operations directly into your LangChain workflows for automated, data-driven map updates.

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Connect Felt (Collaborative Maps) MCP to LangChain

Create your Vinkius account to connect Felt (Collaborative Maps) 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 Felt (Collaborative Maps) with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Sequence Felt (Collaborative Maps) actions in LangChain

Feed the output of your geographic analysis straight into `add_elements` to update your maps. Your agent handles the logic, moving data from SQL or vector stores into your collaborative workspace. Each step is traceable. You see exactly what your agent pushed to the map and when, keeping your pipeline transparent.

Dynamic map construction with LangChain

Use `create_map` as a tool within a ReAct loop to generate new workspaces on the fly. Your agent decides the map title and scope based on the user's specific project requirements. Once the map exists, chain the output ID into `create_layer` to import your GeoJSON or CSV files. It puts your data exactly where it needs to be without manual file handling.

Automated map maintenance

Trigger `update_element` or `delete_element` based on changing conditions in your data. If your external sensor feed detects a change, the agent updates the map state immediately. This keeps your collaborative view current. Your team sees the latest data points without you needing to manually refresh or push updates.

Setup guide

Set up Felt (Collaborative Maps) 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 Felt (Collaborative Maps) 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({
    "felt-collaborative-maps-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 Felt (Collaborative Maps) transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Felt. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Felt (Collaborative Maps) MCP in LangChain

Install the necessary adapters and initialize the MCP client with your server endpoint. You then fetch the tools and register them with your agent to start executing commands.

Yes, you can chain multiple tools to perform complex tasks. For example, your agent can call `get_map` to verify status before running `update_layer` to apply new styles.

The server operates within a secure sandbox environment. Your credentials remain isolated, and only the specific tool operations you authorize are executed.

The server remains stateless by default. You should use a persistent session to maintain context if your workflow requires multiple sequential interactions.

Your geographic data and map configurations never leave the secure transport layer. The MCP server only processes the specific coordinates and metadata required for your requested map operations.

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