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Felt (Collaborative Maps) MCP Server for AutoGenGive AutoGen instant access to 11 tools to Add Elements, Create Layer, Create Map, and more

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Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Felt (Collaborative Maps) as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

Ask AI about this MCP Server for AutoGen

The Felt (Collaborative Maps) MCP Server for AutoGen is a standout in the Collaboration category — giving your AI agent 11 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="felt_collaborative_maps_agent",
            tools=tools,
            system_message=(
                "You help users with Felt (Collaborative Maps). "
                "11 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())
Felt (Collaborative Maps)
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Felt (Collaborative Maps) MCP Server

Connect Felt to your AI agent to take full control of your collaborative mapping workflows through natural conversation. This server allows you to manage maps, layers, and geographic elements without leaving your workspace.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Felt (Collaborative Maps) tools. Connect 11 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

What you can do

  • Map Management — List all accessible maps, create new ones with specific viewports, and retrieve detailed metadata or delete maps.
  • Data Uploads & Layers — Create layers by uploading geographic data (GeoJSON, CSV, KML) via public URLs and monitor their processing status.
  • Dynamic Styling — Update layer names and apply complex visual styles using the Felt Style Object (FSO) programmatically.
  • Element Manipulation — Add, update, or delete specific geographic features like points, lines, and polygons within your map layers.
  • Spatial Analysis Context — Fetch map and layer details to provide your AI with the necessary context for spatial reasoning.

The Felt (Collaborative Maps) MCP Server exposes 11 tools through the Vinkius. Connect it to AutoGen in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 Felt (Collaborative Maps) tools available for AutoGen

When AutoGen connects to Felt (Collaborative Maps) through Vinkius, your AI agent gets direct access to every tool listed below — spanning gis, mapping, spatial-data, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

add

Add elements on Felt (Collaborative Maps)

Add elements to a Felt layer

create

Create layer on Felt (Collaborative Maps)

Supports GeoJSON, CSV, KML, Shapefiles, etc. Create a layer (Upload Data) to a Felt map

create

Create map on Felt (Collaborative Maps)

Create a new Felt map

delete

Delete element on Felt (Collaborative Maps)

Delete a Felt element

delete

Delete layer on Felt (Collaborative Maps)

Delete a Felt layer

delete

Delete map on Felt (Collaborative Maps)

Delete a Felt map

get

Get layer on Felt (Collaborative Maps)

Get details for a specific Felt layer

get

Get map on Felt (Collaborative Maps)

Get details for a specific Felt map

list

List maps on Felt (Collaborative Maps)

List Felt maps

update

Update element on Felt (Collaborative Maps)

Update a Felt element

update

Update layer on Felt (Collaborative Maps)

Update a Felt layer

Connect Felt (Collaborative Maps) to AutoGen via MCP

Follow these steps to wire Felt (Collaborative Maps) into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install AutoGen

Run pip install "autogen-ext[mcp]"
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration
04

Explore tools

The workbench discovers 11 tools from Felt (Collaborative Maps) automatically

Why Use AutoGen with the Felt (Collaborative Maps) MCP Server

AutoGen provides unique advantages when paired with Felt (Collaborative Maps) through the Model Context Protocol.

01

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Felt (Collaborative Maps) tools to solve complex tasks

02

Role-based architecture lets you assign Felt (Collaborative Maps) tool access to specific agents. a data analyst queries while a reviewer validates

03

Human-in-the-loop support: agents can pause for human approval before executing sensitive Felt (Collaborative Maps) tool calls

04

Code execution sandbox: AutoGen agents can write and run code that processes Felt (Collaborative Maps) tool responses in an isolated environment

Felt (Collaborative Maps) + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Felt (Collaborative Maps) MCP Server delivers measurable value.

01

Collaborative analysis: one agent queries Felt (Collaborative Maps) while another validates results and a third generates the final report

02

Automated review pipelines: a researcher agent fetches data from Felt (Collaborative Maps), a critic agent evaluates quality, and a writer produces the output

03

Interactive planning: agents negotiate task allocation using Felt (Collaborative Maps) data to make informed decisions about resource distribution

04

Code generation with live data: an AutoGen coder agent writes scripts that process Felt (Collaborative Maps) responses in a sandboxed execution environment

Example Prompts for Felt (Collaborative Maps) in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Felt (Collaborative Maps) immediately.

01

"List all my current Felt maps."

02

"Create a new map titled 'Project Alpha' centered on San Francisco."

03

"Add a point element to layer `layer_abc` at [ -122.4, 37.8 ]."

Troubleshooting Felt (Collaborative Maps) MCP Server with AutoGen

Common issues when connecting Felt (Collaborative Maps) to AutoGen through Vinkius, and how to resolve them.

01

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Felt (Collaborative Maps) + AutoGen FAQ

Common questions about integrating Felt (Collaborative Maps) MCP Server with AutoGen.

01

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Felt (Collaborative Maps) tools during their conversation turns.
02

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.
03

Does AutoGen support human approval for tool calls?

Yes. Configure human-in-the-loop mode so agents pause and request approval before executing sensitive MCP tool calls.

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