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Scribe MCP Server for Pydantic AIGive Pydantic AI instant access to 10 tools to Check Scribe Status, Get Documentation Stats, Get Recent Documents, and more

Built by Vinkius GDPR 10 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The Scribe app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Scribe "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())
Scribe
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
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<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 Scribe MCP Server

Connect your Scribe organization to any AI agent and access your process documentation library through natural conversation.

Pydantic AI validates every Scribe 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

  • Full Search — Search across all Scribes and Knowledge Pages simultaneously.
  • Filtered Search — Search only guides or only pages for targeted results.
  • Team Scoping — Find documents within a specific team for departmental queries.
  • Date Filtering — Search by creation date range or get recent documents.
  • Teams — List all teams and their documents for content auditing.
  • Statistics — Get an overview of your documentation footprint.

The Scribe 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.

All 10 Scribe tools available for Pydantic AI

When Pydantic AI connects to Scribe through Vinkius, your AI agent gets direct access to every tool listed below — spanning scribe, process-documentation, knowledge-base, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

check_scribe_status

Verify Scribe API connectivity

get_documentation_stats

Get documentation statistics

get_recent_documents

Get documents created in the last 30 days

get_team_documents

Useful for auditing team documentation. Get all documents for a specific team

list_teams

List all teams in your Scribe organization

search_by_date

Dates should be in YYYY-MM-DD format. Search documents by creation date range

search_by_team

Search documents within a specific team

search_documents

Search across all Scribes and Pages

search_pages

Search only Knowledge Pages

search_scribes

Search only Scribe guides

Connect Scribe to Pydantic AI via MCP

Follow these steps to wire Scribe into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 10 tools from Scribe with type-safe schemas

Why Use Pydantic AI with the Scribe MCP Server

Pydantic AI provides unique advantages when paired with Scribe through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Scribe integration code

03

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

04

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

Scribe + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Scribe in Pydantic AI

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

01

"Search for all documentation about 'onboarding'."

02

"List all teams in our Scribe organization."

03

"What documents were created in the last 30 days?"

Troubleshooting Scribe MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Scribe + Pydantic AI FAQ

Common questions about integrating Scribe MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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