How do I get a Cody AI API key?

In the Cody AI dashboard, go to **Settings > API** and copy your key. Paste it below.

Focus Mode restricts a bot's knowledge to specific documents for a given conversation, improving answer relevance.

How long does it take to learn new documents?

Usually seconds to minutes depending on document size. Use 'get_document_status' to check when sync is complete.

Cody AI MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Cody AI
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Cody AI through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Cody AI "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Cody AI?"
    )
    print(result.data)

asyncio.run(main())

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 Cody AI MCP Server

Connect your AI to Cody AI, the business AI assistant that can be trained on your own knowledge base.

Pydantic AI validates every Cody AI 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

Bot Management — List active bots, check their configurations, and view which documents they're trained on.
Conversations — Start conversations with any bot and ask questions against your knowledge base.
Document Import — Import web pages and files into specific folders to expand a bot's knowledge.

The Cody AI 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 Cody AI to Pydantic AI via MCP

Follow these steps to integrate the Cody AI 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 Cody AI with type-safe schemas

Why Use Pydantic AI with the Cody AI MCP Server

Pydantic AI provides unique advantages when paired with Cody AI 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 Cody AI integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Cody AI connection logic from agent behavior for testable, maintainable code

Cody AI + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Cody AI MCP Server delivers measurable value.

Type-safe data pipelines: query Cody AI with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Cody AI tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Cody AI and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Cody AI responses and write comprehensive agent tests

Cody AI MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Cody AI to Pydantic AI via MCP:

create_conversation

Create a new conversation session with a specific bot

get_bot_details

Retrieve detailed information about a specific bot

get_document_status

Check the syncing status of a document to see if the AI has finished learning it

import_webpage

Import content from a URL into a specific folder in your knowledge base

list_bots

Retrieve all bots configured in your Cody AI account

list_conversations

Retrieve a list of recent conversations

list_documents

Retrieve a list of documents in your knowledge base

list_folders

Retrieve a list of folders in your knowledge base

list_messages

Retrieve the message history for a specific conversation

send_message

Send a prompt to the AI in a specific conversation

Example Prompts for Cody AI in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Cody AI immediately.

"Show me all active bots in Cody AI."

"Ask bot 'bot-xxxx': 'How do I reset my password?'"

"Import my local 'compliance_guidelines.pdf' into the Legal Bot's knowledge base."

Troubleshooting Cody AI MCP Server with Pydantic AI

Common issues when connecting Cody AI to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Cody AI + Pydantic AI FAQ

Common questions about integrating Cody AI MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Cody AI MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.