About ChipsAI MCP Server
ChipsAI MCP Server connects MCP clients to ChipsBot for managing chatbots, conversations, documents, routing, and AI models. It also exposes per-bot RAG configuration and analytics tools.
Key features
- 01Create and manage chatbots
- 02Manage conversations and widget history
- 03Upload documents for RAG
- 04Configure bot-to-bot routing
- 05Adjust per-bot RAG settings
- 06Inspect analytics, plans, and models
Use cases
- 01Set up a chatbot and upload reference documents
- 02Review chatbot conversations and usage analytics
- 03Route questions from an orchestrator to specialist bots
- 04Tune retrieval settings for a chatbot
MCP support
Exposes ChipsBot management, chat, document, analytics, routing, and model tools to MCP clients such as Claude Code and Claude Desktop. Authentication uses a ChipsAI API key or legacy username and password.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
uvx chipsai-mcpCHIPSAI_EMAILChipsAI account emailCHIPSAI_PASSWORDSecretChipsAI account passwordLocal servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEChipsAI MCP Server
MCP (Model Context Protocol) server for ChipsBot — manage chatbots, conversations, documents, bot-to-bot routing, RAG configuration, and AI models from Claude Code, Claude Desktop, or any MCP client.
Requirements
Quick Start
No installation needed with uv:
uv run --script server.py
Or install manually:
pip install "mcp[cli]" httpx
python server.py
Configuration
The server uses environment variables for authentication. API key is the recommended method — generate one from your ChipsBot dashboard.
| Variable | Description | Default |
|---|---|---|
CHIPSAI_API_KEY | Your ChipsAI API key (recommended) | — |
CHIPSAI_API_URL | API base URL | https://ai.chipsbuilder.com |
Legacy: username/password authentication
If you don't have an API key, you can use username/password instead:
| Variable | Description |
|---|---|
CHIPSAI_USERNAME | Your ChipsAI username |
CHIPSAI_PASSWORD | Your ChipsAI password |
Claude Code
Add to your project's .mcp.json:
{
"mcpServers": {
"chipsai": {
"command": "uvx",
"args": ["chipsai-mcp"],
"env": {
"CHIPSAI_API_KEY": "chipsai_your_api_key_here"
}
}
}
}
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"chipsai": {
"command": "uvx",
"args": ["chipsai-mcp"],
"env": {
"CHIPSAI_API_KEY": "chipsai_your_api_key_here"
}
}
}
}
Available Tools
Chatbot Management
| Tool | Description |
|---|---|
list_chatbots | List all chatbots for the authenticated user |
get_chatbot | Get full chatbot details (prompt, model, colors, etc.) |
create_chatbot | Create a new chatbot (returns embed script tag) |
update_chatbot | Update chatbot fields (name, prompt, model, theme, colors, etc.) |
delete_chatbot | Soft-delete (deactivate) a chatbot |
get_chatbot_config | Get public widget configuration |
get_chatbot_analytics | Get analytics: messages, sessions, daily stats, devices, countries |
Documents (RAG)
| Tool | Description |
|---|---|
upload_document | Upload PDF/DOC/DOCX to a chatbot's knowledge base (LlamaParse) |
Conversations
| Tool | Description |
|---|---|
list_conversations | List conversations, optionally filtered by chatbot |
create_conversation | Create a new conversation |
get_conversation | Get conversation details |
update_conversation | Update conversation title |
delete_conversation | Delete a conversation and all messages |
get_conversation_messages | Get all messages from a conversation |
Widget History
| Tool | Description |
|---|---|
list_conversation_history | List widget conversation sessions (paginated, filter by chatbot) |
get_session_messages | Get all messages from a widget conversation session |
Chat
| Tool | Description |
|---|---|
send_message | Send a message and get AI response (auto-creates conversation) |
Bot-to-Bot Connections
| Tool | Description |
|---|---|
connect_bot | Connect a specialist bot to an orchestrator bot (role-based routing) |
list_bot_connections | List all specialist bots connected to an orchestrator |
update_bot_connection | Update role, label, description, or active status of a connection |
disconnect_bot | Remove a bot-to-bot connection |
RAG Configuration
| Tool | Description |
|---|---|
get_rag_config | Get RAG config: threshold, chunk settings, HyDE, L2, reranker, system instructions |
update_rag_config | Update RAG config (threshold, chunk_size, chunk_strategy, HyDE, L2, reranker, etc.) |
User & Models
| Tool | Description |
|---|---|
get_user_plan | Get credit balance, unlimited status, usage stats |
list_ai_models | List available AI models by provider with credit costs |
RAG Pipeline
ChipsBot supports a full Retrieval-Augmented Generation pipeline configurable per-bot:
- Semantic routing (L1): pgvector + Jina Embeddings v3 — routes queries to the best specialist based on cosine similarity (HNSW index)
- HyDE: for sparse/short queries, generates a hypothetical answer with Haiku and re-embeds it for better retrieval
- Chunk injection (L2): at response time, injects only the top-K relevant KB chunks instead of the full prompt — reduces token usage, improves quality
- Reranking: optional Jina cross-encoder reranker (
jina-reranker-v2-base-multilingual) applied after cosine retrieval - Chunking strategies:
char(fixed size),paragraph(semantic\n\nsplit),sentence(.!?split) - Document upload: PDF/DOC/DOCX parsed via LlamaParse, extracted text stored as KB
Use get_rag_config / update_rag_config to tune all parameters per-bot.
Bot-to-Bot Routing
An orchestrator bot can route questions to specialist bots based on role/description. The orchestrator detects [ROUTE:uuid] tags in its own response and delegates to the matching specialist, passing recent chat history as context.
Use connect_bot to link specialists to an orchestrator, list_bot_connections to inspect the routing table, and update_bot_connection to adjust roles or toggle connections on/off.
Credit System
ChipsAI uses a credit-based pricing model:
| Tier | Credits/msg | Models |
|---|---|---|
| Free | 0 | Llama 4 Scout, Llama 3.3 70B, Llama 3.1 8B (Groq) |
| Economy | 0.5 | Mistral Nemo, DeepSeek Chat |
| Standard | 1.0 | GPT-4o-mini, Gemini 2.5 Flash, Mistral Small, Claude Haiku 4.5 |
| Premium | 2.0 | GPT-4o, Mistral Large, DeepSeek Reasoner |
| Top | 3.0 | GPT-4.1, Claude Sonnet 4.6, Gemini 2.5 Pro |
Credit packages: 150 credits for €5 | 700 for €20 | 2000 for €50. Credits never expire. Bring your own API key to use any model for free (no credits consumed).
Usage Examples
Once configured, use natural language in Claude:
- "List my chatbots"
- "Create a chatbot called Support Bot"
- "Upload the product catalog PDF to my chatbot"
- "Send a test message to my chatbot"
- "Show analytics for the last 7 days"
- "Change the chatbot model to Claude Sonnet 4.6"
- "What's my credit balance?"
- "What AI models are available?"
- "Connect the billing bot as a specialist of my main orchestrator"
- "List all specialist bots connected to my orchestrator"
- "Show the RAG config for my chatbot"
- "Set the RAG threshold to 0.5 and enable reranking"
- "Enable L2 chunk injection with top_k=5"
Authentication
API Key (recommended): Set CHIPSAI_API_KEY with a key generated from your dashboard. The key is sent as a Bearer token — no token management needed.
JWT (legacy): If using username/password, tokens are obtained via JWT and refreshed transparently.
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.