How to integrate Highergov MCP with LangChain

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Introduction

This guide walks you through connecting Highergov to LangChain using the Composio tool router. By the end, you'll have a working Highergov agent that can list recent federal contract awards for it services, show all active dla contract opportunities today, retrieve grant history for a specific agency, download documents linked to a contract award through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Highergov account through Composio's Highergov MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Highergov project to Composio
  • Create a Tool Router MCP session for Highergov
  • Initialize an MCP client and retrieve Highergov tools
  • Build a LangChain agent that can interact with Highergov
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Highergov MCP server, and what's possible with it?

The Highergov MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Highergov account. It provides structured and secure access to government contracting and grant intelligence, so your agent can perform actions like searching contracts, analyzing award history, retrieving agency details, and fetching grant data on your behalf.

  • Comprehensive contract search and retrieval: Quickly have your agent look up federal contracts, filter by last modified date, or leverage saved searches to find exactly what you need.
  • Award and grant history analysis: Direct your agent to access detailed award and grant histories, making it simple to track funding trends across agencies or time periods.
  • Agency and program intelligence: Ask your agent to list and explore government agencies, defense programs, or contract vehicles to support your market research.
  • Document and opportunity extraction: Let your agent fetch associated documents or list DLA contract opportunities for deeper due diligence and competitive analysis.
  • IDV and contract vehicle tracking: Monitor Indefinite Delivery Vehicles (IDVs) and contract vehicles to better understand procurement patterns and strategic opportunities.

Supported Tools & Triggers

Tools
Get AgenciesTool to retrieve agencies information.
Get Award HistoryTool to retrieve award history.
Get Contract HistoryTool to retrieve contract history.
Get Contract IDVsTool to retrieve Indefinite Delivery Vehicle (IDV) contract records via the HigherGov Contracts endpoint.
Get ContractsTool to retrieve federal contract data.
Get Contract VehiclesTool to retrieve contract vehicles.
Get Defense ProgramsTool to retrieve defense programs information.
Get DLA Contract OpportunitiesTool to retrieve DLA contract opportunities.
Get DocumentsTool to fetch document metadata from HigherGov.
Get Grant HistoryTool to fetch historical data on grants.
Get Grant OpportunitiesTool to retrieve information on grant opportunities.
Get Grant ProgramsTool to retrieve information on grant programs.
Get NAICS CodesTool to retrieve NAICS codes.
Get OpportunitiesTool to retrieve opportunity data.
Get Opportunity HistoryTool to retrieve opportunity history.
Get PeopleTool to retrieve information on people related to government contracts and grants.
Get Prime Contract AwardsTool to retrieve prime contract awards.
Get Prime Grant AwardsTool to retrieve information on prime grant awards.
Get ProgramsTool to retrieve a list of government programs and categories.
Get Product and Service CodesTool to retrieve information on Product and Service Codes.
Get PursuitsTool to retrieve user-specific pursuits.
Get SBIR OpportunitiesTool to retrieve SBIR (Small Business Innovation Research) opportunities.
Get SLED Contract OpportunitiesTool to retrieve state and local (SLED) contract opportunities.
Get Subcontract AwardsTool to retrieve subcontract awards.
Get Subgrant AwardsTool to retrieve subgrant awards information.
Get Task OrdersTool to retrieve task order data.
Get Tech ProgramsTool to retrieve information on technology programs.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Highergov functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Highergov tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Highergov
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['highergov']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Highergov tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Highergov tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "highergov-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Highergov MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Highergov tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Highergov related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Highergov and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['highergov']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "highergov-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Highergov related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Highergov through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Highergov MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Highergov MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Highergov MCP with Claude Agent SDK

Google ADK

Google ADK

Use Highergov MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Highergov MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Highergov MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Highergov MCP with LlamaIndex

CrewAI

CrewAI

Use Highergov MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Highergov MCP?

With a standalone Highergov MCP server, the agents and LLMs can only access a fixed set of Highergov tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Highergov and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Highergov tools.

Can I manage the permissions and scopes for Highergov while using Tool Router?

Yes, absolutely. You can configure which Highergov scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Highergov data and credentials are handled as safely as possible.

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