How to Use the CrowdTangle MCP in Pydantic AI

Q: Is the CrowdTangle MCP server compatible with Pydantic AI?

Yes, use the MCPToolset class to connect to the HTTP endpoint. It supports the standard SSE and Streamable HTTP transports required by the framework.

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Connect CrowdTangle MCP to Pydantic AI

Create your Vinkius account to connect CrowdTangle to Pydantic AI 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 CrowdTangle with Pydantic AI

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Validated Social Data for Pydantic AI

Define Pydantic models for every `get_post_details` response to ensure your agent never processes malformed data. If the API returns unexpected fields, the agent stops immediately. This prevents silent errors from propagating through your logic. You gain confidence that every interaction metric your agent handles meets your strict schema requirements.

Query CrowdTangle Lists with Pydantic AI

Fetch and validate your tracking lists using `list_monitored_lists` to keep your agent's knowledge base accurate. The agent maps the list metadata to your typed classes upon receipt. This structure makes it easy to manage multiple lists simultaneously. Your code remains clean because the agent handles the validation at the boundary.

Measure Post Performance with Pydantic AI

Use `get_top_performing_posts` to compare actual vs. expected interaction scores. Pydantic AI validates the resulting performance metrics before the agent makes any further decisions. Your logic relies on verified numbers rather than guessed data. This approach ensures your agent's reporting remains consistent and reliable over time.

Setup guide

Set up CrowdTangle MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "crowdtangle-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to CrowdTangle tools.",
)

result = await agent.run("List recent CrowdTangle transactions")
print(result.output)

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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 CrowdTangle. 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 CrowdTangle MCP in Pydantic AI

Every tool output is cast against your Pydantic schemas immediately after the server returns it. If the data doesn't match your model, the agent triggers a validation error.

Yes, use the `MCPToolset` class to connect to the HTTP endpoint. It supports the standard SSE and Streamable HTTP transports required by the framework.

Your API tokens are managed at the Vinkius gateway level. The agent only receives the validated data it needs, keeping your configuration settings encrypted.

The agent will raise a validation error instead of hallucinating values. This forces your system to handle the unexpected input explicitly.

All social media account metadata is ephemeral. The server does not persist your data, and each request is scoped to your unique session token.

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