DevCycle MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect DevCycle through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to DevCycle "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in DevCycle?"
)
print(result.data)
asyncio.run(main())
* 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 DevCycle MCP Server
Integrate DevCycle, the modern feature flag and experimentation platform, directly into your AI workflow. Manage your feature flags across projects, monitor staging and production environments, and audit targeting rules and variations using natural language.
Pydantic AI validates every DevCycle tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Feature Flag Management — List, search, and retrieve detailed configuration for all your feature flags.
- Environment Oversight — Monitor project environments, retrieve SDK keys, and track deployment statuses.
- Variable & Variation Tracking — List all defined variables and their variations to ensure technical consistency.
- Operational Control — Update feature flag statuses (active/archived) directly via chat.
The DevCycle MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect DevCycle to Pydantic AI via MCP
Follow these steps to integrate the DevCycle MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from DevCycle with type-safe schemas
Why Use Pydantic AI with the DevCycle MCP Server
Pydantic AI provides unique advantages when paired with DevCycle through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your DevCycle integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your DevCycle connection logic from agent behavior for testable, maintainable code
DevCycle + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the DevCycle MCP Server delivers measurable value.
Type-safe data pipelines: query DevCycle with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple DevCycle tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query DevCycle and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock DevCycle responses and write comprehensive agent tests
DevCycle MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect DevCycle to Pydantic AI via MCP:
get_environment_sdk_keys
List SDK keys for all environments in a project
get_feature_flag_details
Get full configuration and targeting rules for a specific feature flag
get_project_details
Get detailed information for a specific DevCycle project
list_active_flags
Identify feature flags that are currently active
list_devcycle_projects
List all projects in your DevCycle account
list_feature_flags
g. release, ops), and current statuses. List all feature flags within a specific project
list_feature_variables
List all variables defined in a project
list_project_environments
List all environments (e.g. Production, Staging) for a project
search_feature_flags
Search for feature flags in a project by keyword
update_feature_flag_status
Update the status (e.g. active, archived) of a feature flag
Example Prompts for DevCycle in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with DevCycle immediately.
"List all feature flags in the project 'Main-App'."
"Show me the configuration for the 'Beta-Feature' flag."
"What are the SDK keys for our 'Production' environment?"
Troubleshooting DevCycle MCP Server with Pydantic AI
Common issues when connecting DevCycle to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiDevCycle + Pydantic AI FAQ
Common questions about integrating DevCycle MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect DevCycle with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect DevCycle to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.