Connectto Linear, Postgres, Klavis ReportGen MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Linear, Postgres, Klavis ReportGen with Claude's advanced reasoning capabilities in Klavis AI.
Linear
Linear is a modern issue tracking and project management tool designed for high-performance teams to build better software faster
Available Tools:
- linear_get_teams
- linear_get_issues
- linear_get_issue_by_id
- +9 more tools
Postgres
PostgreSQL is a powerful, open source object-relational database system
Available Tools:
- query
Klavis ReportGen
Generate visually appealing JavaScript web reports from search queries with Klavis AI.
Available Tools:
- generate_web_reports
Quick Setup Guide
Follow these steps to connect Claude to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform and get your API keys.
Configure Connections
Add your desired MCP servers to Claude and configure authentication settings with your Anthropic API key.
Test & Deploy
Verify your connections work correctly with Claude's function calling and start using your enhanced AI capabilities.
Claude + KlavisAI Integration Snippets
import os
import json
from anthropic import Anthropic
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
anthropic_client = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
# Constants
CLAUDE_MODEL = "claude-3-5-sonnet-20241022"
user_message = "Your message here"
linear_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.LINEAR,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
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,
)
klavis_reportgen_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.KLAVIS_REPORTGEN,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get tools from all MCP servers
linear_tools = klavis_client.mcp_server.list_tools(
server_url=linear_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.ANTHROPIC,
)
postgres_tools = klavis_client.mcp_server.list_tools(
server_url=postgres_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.ANTHROPIC,
)
klavis_reportgen_tools = klavis_client.mcp_server.list_tools(
server_url=klavis_reportgen_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.ANTHROPIC,
)
# Combine all tools
all_tools = []
all_tools.extend(linear_tools.tools)
all_tools.extend(postgres_tools.tools)
all_tools.extend(klavis_reportgen_tools.tools)
messages = [
{"role": "user", "content": user_message}
]
response = anthropic_client.messages.create(
model=CLAUDE_MODEL,
max_tokens=4000,
messages=messages,
tools=all_tools
)Frequently Asked Questions
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