How to Use the LaunchDarkly MCP in Pydantic AI

Q: Can Pydantic AI agents use LaunchDarkly metrics?

Yes. Calling listmetrics returns data that your agent can validate against your defined schema. It ensures your experiments are tracked with high precision.

Q: How does the MCP Server handle projects in Pydantic AI?

It fetches project lists via listprojects, which your agent then uses to select the correct project key for all other operations.

Use Pydantic AI with LaunchDarkly to ensure your flag data is always validated and type-safe.

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Connect LaunchDarkly MCP to Pydantic AI

Create your Vinkius account to connect LaunchDarkly 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 LaunchDarkly with Pydantic AI

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Type-safe flag access for Pydantic AI

Every response from `get_feature_flag` is validated against your Pydantic models at runtime. If the API returns something unexpected, your agent fails fast instead of proceeding with bad data. This strict validation ensures your agent logic is sound. It uses `list_feature_flags` to populate your agent's state with correctly typed flag objects.

Validate LaunchDarkly audit logs in Pydantic AI

Your agent processes audit logs via `list_audit_logs` with full schema enforcement. It prevents silent errors by checking that every log entry matches your expected structure. This approach gives you total confidence in the data your agent uses for decision making. It transforms raw log output into validated, structured objects your Pydantic AI agent can trust.

Manage deployment environments with MCP Server

Use `list_environments` to get a validated list of your deployment targets. It keeps your agent's environment awareness aligned with your actual infrastructure. Calling `get_environment` provides the specific context your agent needs to operate safely. With Pydantic AI, you know that the environment object received is exactly what your system expects.

Setup guide

Set up LaunchDarkly 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": {
        "launchdarkly-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about LaunchDarkly MCP in Pydantic AI

Install the pydantic-ai-slim package, set up your MCPToolset with the server URL, and pass it to your agent. All tool responses are automatically validated.

Your agent will raise a validation error immediately. This stops the agent from taking any action based on corrupted or unexpected flag configurations.

Yes. Calling `list_metrics` returns data that your agent can validate against your defined schema. It ensures your experiments are tracked with high precision.

It fetches project lists via `list_projects`, which your agent then uses to select the correct project key for all other operations.

The server acts as a strictly typed conduit for your flag and audit data. It enforces schema validation on every request, ensuring that only the expected configuration records enter your agent's memory.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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