@lakehouse/mcp-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@@lakehouse/mcp-server search for revenue reports"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@lakehouse/mcp-server
Model Context Protocol (MCP) server for Lakehouse42.
Features
Code-First Pattern - On-demand tool discovery (~98% token reduction)
Tool Tagging - Filter tools by category (read/write/admin/search/time-travel)
Cursor Pagination - Efficient browsing of large result sets
Streamable HTTP - Scalable deployment with session recovery
Optimized Responses - Compact JSON, truncated snippets, sample rows
Related MCP server: IcebergMCP
Quick Start
LAKEHOUSE42_API_KEY=lh_xxx npx @lakehouse/mcp-serverClaude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"lakehouse42": {
"command": "npx",
"args": ["@lakehouse/mcp-server"],
"env": {
"LAKEHOUSE42_API_KEY": "lh_your_api_key"
}
}
}
}Environment Variables
Variable | Required | Default |
| Yes | - |
| No |
|
Tools
search_tools
Discover tools on-demand (code-first pattern).
{ "tags": ["search"], "detail": "summary" }Parameter | Type | Description |
| string | Search term |
| string[] |
|
| string |
|
search
Hybrid search with cursor pagination.
{ "query": "revenue report", "top_k": 10 }Returns: 5 results max, 200-char snippets, next_cursor for pagination.
ask_question
RAG-powered Q&A.
{ "question": "What is our refund policy?" }Returns: answer + source count.
get_document / list_documents / list_collections
Document and collection management with cursor pagination.
upload_document
Upload text documents (auto-chunked and indexed).
time_travel_query / time_travel_diff / list_snapshots
Iceberg time-travel queries. Returns row count + 3 sample rows.
HTTP Transport
For web deployments:
import { HttpTransport, ToolExecutor, ApiClient } from '@lakehouse/mcp-server';
const client = new ApiClient({ apiKey: 'lh_xxx', baseUrl: 'https://api.lakehouse42.com' });
const transport = new HttpTransport({ toolExecutor: new ToolExecutor(client) });
http.createServer((req, res) => transport.handleRequest(req, res)).listen(3000);Features:
Session management (
Mcp-Session-Idheader)SSE streaming (
Accept: text/event-stream)Disconnect recovery (
Last-Event-ID)
Endpoints:
POST /mcp- JSON-RPC requestsGET /mcp- SSE streamDELETE /mcp- Close sessionGET /health- Health check
Programmatic Usage
import { createServer, searchTools, TAGGED_TOOLS } from '@lakehouse/mcp-server';
// Stdio server
const server = createServer({ apiKey: 'lh_xxx' });
await server.start();
// Tool discovery
const readTools = searchTools(undefined, ['read'], 'name');
// → [{ name: 'search' }, { name: 'ask_question' }, ...]Response Optimization
Tool | Optimization |
search | 5 results, 200-char snippets |
list_documents | 10 docs, essential fields |
time_travel_query | 3 sample rows + count |
All responses use compact JSON (no pretty-printing).
License
MIT
Available Tools
10 toolsask_questionC
RAG-based Q&A. Returns AI answer with source count.
Inputs: question (required), model, collection_ids.
get_documentB
Get document by ID. Optionally include full content.
Inputs: document_id (required), include_content.
list_collectionsB
List all collections. Cursor pagination.
Inputs: limit, cursor.
list_documentsC
List documents with filters. Cursor pagination.
Inputs: limit, cursor, search, status, +1 more.
list_snapshotsB
List Iceberg table snapshots for time-travel.
Inputs: table_name (required), limit, namespace.
searchB
Hybrid search (dense+sparse+BM25). Returns ranked chunks with cursor pagination.
Inputs: query (required), top_k, cursor, rerank, +1 more.
search_toolsA
Find available tools by name, tag, or description. Returns tool info at specified detail level.
Inputs: tags, query, detail.
time_travel_diffB
Compare two snapshots. Returns added/deleted/changed counts.
Inputs: table_name (required), to_snapshot_id (required), from_snapshot_id (required), namespace.
time_travel_queryC
Query historical Iceberg data at snapshot/timestamp.
Inputs: table_name (required), limit, where, columns, +3 more.
upload_documentB
Upload text document. Auto-chunked and indexed.
Inputs: title (required), content (required), metadata, content_type, +1 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 10 tools
Tools are largely distinct: search_tools is meta, search and ask_question target different retrieval modes, and time_travel tools are clearly separated. Some confusion could arise between search and ask_question since both retrieve information, but descriptions clarify the intent.
Most tools follow a verb_noun pattern (get_document, list_documents, upload_document). A few deviate like 'search' (bare verb) and 'time_travel_diff' (noun-heavy), but overall naming is predictable and readable.
With 10 tools, the server is well-scoped. Each tool serves a distinct function within the two core domains (document search/RAG and time-travel on Iceberg), and none feel redundant or unnecessary.
The document side covers upload, retrieval, and search but lacks update and delete operations, which are common CRUD gaps. The time-travel features are useful but assume knowledge of tables/snapshots without a listing mechanism; overall the surface is functional but not fully comprehensive.
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