Bring Gis
to CrewAI
Learn how to connect Felt (Collaborative Maps) to CrewAI and start using 11 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the 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.
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.
How it works
- Subscribe to this server
- Enter your Felt API Token
- Start building and editing maps from Claude, Cursor, or any MCP-compatible client
Who is this for?
- GIS Analysts & Data Scientists — quickly prototype maps and upload datasets for visualization using simple commands.
- Urban Planners & Researchers — manage collaborative project maps and update elements as field data comes in.
- Logistics & Ops Teams — visualize routes and service areas by programmatically adding elements to shared maps.
Built-in capabilities (11)
Add elements to a Felt layer
Supports GeoJSON, CSV, KML, Shapefiles, etc. Create a layer (Upload Data) to a Felt map
Create a new Felt map
Delete a Felt element
Delete a Felt layer
Delete a Felt map
Get details for a specific Felt layer
Get details for a specific Felt map
List Felt maps
Update a Felt element
Update a Felt layer
Why CrewAI?
When paired with CrewAI, Felt (Collaborative Maps) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Felt (Collaborative Maps) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Felt (Collaborative Maps) in CrewAI
Felt (Collaborative Maps) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Felt (Collaborative Maps) to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Felt (Collaborative Maps) in CrewAI
The Felt (Collaborative Maps) 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. All 11 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Felt (Collaborative Maps) for CrewAI
Every tool call from CrewAI to the Felt (Collaborative Maps) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I upload my own geographic data files to a map?
Yes! Use the create_layer tool by providing a public URL to your GeoJSON, CSV, or KML file. The server will initiate the upload and processing into your specified Felt map.
How do I add a specific point or shape to an existing layer?
You can use the add_elements tool. Simply provide the layer_id and a JSON array of GeoJSON features (points, lines, or polygons) you want to add to that layer.
Is it possible to change the visual style of a map layer?
Yes. Use the update_layer tool and provide a 'Felt Style Object' (FSO) in the style parameter to programmatically change colors, icons, or visibility rules.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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