Greptile MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Delete Repository, Get File Info, Get Greptile Usage, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Greptile 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 Greptile app connector for Pydantic AI is a standout in the Developer Tools category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Greptile "
"(11 tools)."
),
)
result = await agent.run(
"What tools are available in Greptile?"
)
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 Greptile MCP Server
Connect your Greptile account to any AI agent and unlock AI-powered codebase understanding through natural conversation.
Pydantic AI validates every Greptile tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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
- AI Codebase Q&A — Ask natural language questions about one or more repositories and receive AI-generated answers with code references
- Contextual Follow-ups — Continue conversations with session context for multi-turn codebase exploration
- Semantic Code Search — Search across indexed repositories to find relevant files, functions, and code patterns
- File-Specific Search — Target searches within a specific file path for precise results
- Repository Indexing — Submit GitHub or GitLab repositories for indexing, check progress, and trigger re-indexing
- Repository Management — List all indexed repos, inspect file metadata, and remove outdated indexes
- Usage Monitoring — Track API consumption and rate limits
The Greptile MCP Server exposes 11 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 11 Greptile tools available for Pydantic AI
When Pydantic AI connects to Greptile through Vinkius, your AI agent gets direct access to every tool listed below — spanning codebase-intelligence, semantic-search, repository-indexing, 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.
Delete indexed repository
Get file info
Check API usage
Get repository status
Index a repository
List indexed repositories
Query codebase with AI
Query with session context
Reindex a repository
Search in specific file
Search codebase
Connect Greptile to Pydantic AI via MCP
Follow these steps to wire Greptile into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Greptile MCP Server
Pydantic AI provides unique advantages when paired with Greptile 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 Greptile integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Greptile connection logic from agent behavior for testable, maintainable code
Greptile + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Greptile MCP Server delivers measurable value.
Type-safe data pipelines: query Greptile with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Greptile tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Greptile and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Greptile responses and write comprehensive agent tests
Example Prompts for Greptile in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Greptile immediately.
"How does the authentication middleware work in our backend repository?"
"Search for all files that import the database connection module and show me the file info."
"Index our new frontend repository and check the indexing status."
Troubleshooting Greptile MCP Server with Pydantic AI
Common issues when connecting Greptile to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiGreptile + Pydantic AI FAQ
Common questions about integrating Greptile 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.