Tettra MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Tettra through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MultiServerMCPClient({
"tettra": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Tettra, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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 Tettra MCP Server
Connect your Tettra internal knowledge base to any AI agent and bring your company's documentation directly into your developer workflow. No more switching tabs to look up API specs or onboarding guides.
LangChain's ecosystem of 500+ components combines seamlessly with Tettra through native MCP adapters. Connect 12 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Deep Search — Perform full-text searches across all your company's Tettra pages to instantly find answers and organizational knowledge
- Knowledge Retrieval — Read the complete markdown/HTML content of any page, technical guide, or team policy natively inside your chat
- Content Creation — Command your agent to draft and publish new wiki pages, or suggest documentation updates on the fly
- Category Navigation — Browse through your team's top-level categories, root folders, and subcategories visually
- Q&A Management — Post new questions to your team's internal Q&A board or list unanswered questions right from your IDE
The Tettra MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain 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 Tettra to LangChain via MCP
Follow these steps to integrate the Tettra MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 12 tools from Tettra via MCP
Why Use LangChain with the Tettra MCP Server
LangChain provides unique advantages when paired with Tettra through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Tettra MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Tettra queries for multi-turn workflows
Tettra + LangChain Use Cases
Practical scenarios where LangChain combined with the Tettra MCP Server delivers measurable value.
RAG with live data: combine Tettra tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Tettra, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Tettra tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Tettra tool call, measure latency, and optimize your agent's performance
Tettra MCP Tools for LangChain (12)
These 12 tools become available when you connect Tettra to LangChain via MCP:
create_qa_question
Posts a new question in the Tettra Q&A system
create_wiki_page
Provide title, content, and category ID. Creates a new wiki page in a specific category
get_category_details
Retrieves details for a specific Tettra category
get_page_content
Returns title and Markdown/HTML body. Retrieves the full content and metadata of a specific Tettra page
list_categories
Lists all top-level categories in the Tettra wiki
list_pages_in_category
Lists all wiki pages within a specific category
list_qa_questions
Lists all questions posted in the Tettra Q&A system
list_subcategories
Lists all subcategories under a specific parent category
search_pages
Returns up to 5 matching pages. Full-text search across all Tettra wiki pages
suggest_new_page
Suggests a new wiki page to the team
update_wiki_page
Provide the page ID and the new fields. Updates the title or content of an existing Tettra page
verify_wiki_page
Marks a Tettra page as verified and up-to-date
Example Prompts for Tettra in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Tettra immediately.
"Search the wiki for 'Database Migration Checklist'."
"Create a new wiki page in the 'Support' category explaining how to handle refund requests."
"Mark page ID 883 as verified and up to date."
Troubleshooting Tettra MCP Server with LangChain
Common issues when connecting Tettra to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersTettra + LangChain FAQ
Common questions about integrating Tettra MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Tettra 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 Tettra to LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.