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Connectto Postgres, Firecrawl Deep Research, GitHub MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Postgres, Firecrawl Deep Research, GitHub for enhanced automation capabilities in Klavis AI.

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Postgres icon

Postgres

featured

PostgreSQL is a powerful, open source object-relational database system

Available Tools:

  • query
Firecrawl Deep Research icon

Firecrawl Deep Research

featured

A personal research assistant that analyze sources across the web, based on Firecrawl

Available Tools:

  • firecrawl_deep_research
GitHub icon

GitHub

featured

Enhanced GitHub MCP Server

Available Tools:

  • github_get_me
  • github_get_issue
  • github_search_issues
  • +31 more tools

Quick Setup Guide

Follow these steps to connect Fireworks AI to these MCP servers

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Connections

Add your desired MCP servers to Fireworks AI and configure authentication settings.

3

Test & Deploy

Verify your connections work correctly and start using your enhanced AI capabilities.

Fireworks AI + KlavisAI Integration Snippets

View Documentation
import os
import json
from fireworks.client import Fireworks
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

# Initialize clients
fireworks_client = Fireworks(api_key=os.getenv("FIREWORKS_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

postgres_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.POSTGRES,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

firecrawl_deep_research_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.FIRECRAWL_DEEP_RESEARCH,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

github_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.GITHUB,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Get all MCP tools
postgres_tools = klavis_client.mcp_server.list_tools(
    server_url=postgres_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
firecrawl_deep_research_tools = klavis_client.mcp_server.list_tools(
    server_url=firecrawl_deep_research_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
github_tools = klavis_client.mcp_server.list_tools(
    server_url=github_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(postgres_tools.tools)
all_tools.extend(firecrawl_deep_research_tools.tools)
all_tools.extend(github_tools.tools)

messages = [
    {"role": "system", "content": "You are a helpful assistant with access to multiple data sources."},
    {"role": "user", "content": user_message}
]

response = fireworks_client.chat.completions.create(
    model="accounts/fireworks/models/llama-v3p1-70b-instruct",
    messages=messages,
    tools=all_tools
)

Frequently Asked Questions

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