🔍 🤖 🌐 Ollama Chat with MCP

Name: 🔍 🤖 🌐 Ollama Chat with MCP
Author: redbuilding

@redbuilding

🔍 🤖 🌐 Ollama Chat with MCP について

This app demonstrates use of MCP server and client in a local model chat via Ollama that incorporates web search via Serper.

#mcp #ollama #serper

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

redbuilding

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "ollama-chat-with-mcp": {
      "command": "python",
      "args": [
        "chat_frontend.py"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is 🔍 🤖 🌐 Ollama Chat with MCP?

🔍 🤖 🌐 Ollama Chat with MCP is a modern UI that integrates local (Ollama) and hosted LLMs with intelligent web search, content extraction, SQL, YouTube transcript analysis, HubSpot actions, Python data analysis, Canva design creation, Figma design inspection, Poe multi-model AI, and Codex code scaffolding — all via the Model Context Protocol (MCP). It is built for developers and power users who want to extend local and hosted models with external tools and data sources.

How to use 🔍 🤖 🌐 Ollama Chat with MCP?

Configure the backend with API keys for the desired providers (OpenAI, Anthropic, Google, etc.) and set up MCP services (web search, SQL, YouTube, HubSpot, Python, Canva, Figma, Poe, Codex). The frontend (React) provides a settings screen for API keys and model selection. Conversations and tasks persist in MongoDB.

Key features of 🔍 🤖 🌐 Ollama Chat with MCP

Smart web search with automatic content extraction
Multi‑provider LLM support (Ollama, OpenAI, Anthropic, Google, etc.)
Semantic memory and document knowledge base (ChromaDB)
Autonomous task execution with full MCP tool access
Canva, Figma, Poe, and Codex integrations
Conversation pinning, user profiles, and personalized AI

Use cases of 🔍 🤖 🌐 Ollama Chat with MCP

Design review and handoff using Figma integration
Automated data analysis and visualization from CSV uploads
Multi‑model content generation (text, image, video, audio)
Autonomous task workflows with planning, retries, and verification
Personalized AI assistance with user context and pinned conversations

FAQ from 🔍 🤖 🌐 Ollama Chat with MCP

What LLMs does it support?

Local Ollama models plus hosted providers: OpenAI, Anthropic, Google, OpenRouter, Groq, and SambaNova — all selectable via a unified model picker.

What data storage is used?

MongoDB stores conversation history and user data; ChromaDB with nomic-embed-text embeddings powers semantic memory and the document knowledge base.

What MCP tools are available?

Fifty-five tools across nine modules: web search, SQL (read-only MySQL), YouTube transcripts, HubSpot, Python data analysis, Canva, Figma, Poe, and Codex workspace.

What are the runtime requirements?

Ollama for local models, API keys for hosted providers, a MongoDB instance, and optional tokens for Canva, Figma, and Poe. The backend (FastAPI) and frontend (React) must be running.