Connectto Jira, Discord, Exa MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Jira, Discord, Exa for enhanced automation capabilities in Klavis AI.

Jira icon

Jira

featured

Jira is a project management and issue tracking tool developed by Atlassian

Available Tools:

  • jira_search
  • jira_get_issue
  • jira_search_fields
  • +11 more tools
Discord icon

Discord

featured

Discord is a VoIP and instant messaging social platform

Available Tools:

  • discord_get_server_info
  • discord_list_members
  • discord_create_text_channel
  • +6 more tools
Exa icon

Exa

featured

Exa is an AI-powered search engine designed for AI applications. Use neural search to understand meaning and context, find similar content, get direct answers with citations, and conduct comprehensive research with structured analysis

Available Tools:

  • exa_search
  • exa_get_contents
  • exa_find_similar
  • +2 more tools

Quick Setup Guide

Follow these steps to connect Together 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 Together AI and configure authentication settings.

3

Test & Deploy

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

Together AI + KlavisAI Integration Snippets

import os
import json
from together import Together
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

# Initialize clients
together_client = Together(api_key=os.getenv("TOGETHER_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

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

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

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

# Get all MCP tools
jira_tools = klavis_client.mcp_server.list_tools(
    server_url=jira_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
discord_tools = klavis_client.mcp_server.list_tools(
    server_url=discord_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
exa_tools = klavis_client.mcp_server.list_tools(
    server_url=exa_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(jira_tools.tools)
all_tools.extend(discord_tools.tools)
all_tools.extend(exa_tools.tools)

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

response = together_client.chat.completions.create(
    model="meta-llama/Llama-2-70b-chat-hf",
    messages=messages,
    tools=all_tools
)

Frequently Asked Questions

Everything you need to know about connecting to these MCP servers

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