How do I find my doc and table IDs?

You can find IDs in the document's URL, or use the 'list_docs' and 'list_tables' tools to discover them.

What does 'HTTP 202 Accepted' mean?

Coda processes many changes asynchronously. This status means your request was queued and will be applied shortly.

Can I trigger buttons in Coda?

Many Coda buttons are column actions that can be triggered by updating a row value. So yes, indirectly.

Coda MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Coda
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Coda through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 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({
        "coda": {
            "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 Coda, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Coda MCP Server

Connect your AI to Coda, the collaborative document platform that brings together words, data, and teams.

LangChain's ecosystem of 500+ components combines seamlessly with Coda through native MCP adapters. Connect 10 tools via 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

Document Browsing — List your recent docs and navigate their sections, tables, and pages.
Table Data — Read rows from any Coda table, filter by column values, and update records.
Formula Values — Retrieve the live value of any named formula in a doc for real-time reporting.

The Coda MCP Server exposes 10 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 Coda to LangChain via MCP

Follow these steps to integrate the Coda 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 10 tools from Coda via MCP

Why Use LangChain with the Coda MCP Server

LangChain provides unique advantages when paired with Coda through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Coda 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 Coda queries for multi-turn workflows

Coda + LangChain Use Cases

Practical scenarios where LangChain combined with the Coda MCP Server delivers measurable value.

RAG with live data: combine Coda tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Coda, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Coda tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Coda tool call, measure latency, and optimize your agent's performance

Coda MCP Tools for LangChain (10)

These 10 tools become available when you connect Coda to LangChain via MCP:

delete_rows

Delete one or more rows from a Coda table

get_doc_details

Retrieve detailed information about a specific Coda document

get_formula_value

Retrieve the current calculated value of a named formula

insert_rows

Insert new rows into a Coda table

list_columns

Retrieve a list of columns in a Coda table

list_docs

Retrieve a list of Coda documents available to you

list_formulas

Retrieve a list of named formulas in a Coda document

list_rows

Retrieve rows from a specific table in a Coda document

list_tables

Retrieve a list of tables within a specific Coda document

update_row

Update an existing row in a Coda table

Example Prompts for Coda in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Coda immediately.

"Show me my recent documents in Coda."

"Get the current value of formula 'TotalBudget' in doc 'doc-yyyy'."

"Check the status of task 'Q3 Launch' in our Sprint Board table."

Troubleshooting Coda MCP Server with LangChain

Common issues when connecting Coda to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Coda + LangChain FAQ

Common questions about integrating Coda MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.