Searchcraft MCP Server

The Searchcraft MCP Server provides a suite of tools for managing your Searchcraft cluster's Documents, Indexes, Federations, Access Keys, and Analytics. It enables MCP Clients, like Claude Desktop, to be prompted in plain English to perform administrative actions like setting up search indexes, access keys, ingesting documents, viewing analytics, searching indexes, and more.

Sample Prompts

Here is a sample prompt that could be used once Claude is connected to the Searchcraft MCP Server.

I'd like to create a product search application using the create_vite_app tool. Please use this JSON dataset https://dummyjson.com/products First use the Searchcraft create_index_from_json tool to create the index and add the documents. Then create an API read key for the vite app using the create_key tool. App details: - App name: "my-ecommerce-app" - Endpoint: http://localhost:8000 - Index name: my-ecommerce-app

Available Tools

The Searchcraft MCP Server currently provides three categories of tools, import tools, engine api tools, and app generation tools:

Engine API Tools

These tools provide direct access to your Searchcraft cluster's core functionality for managing indexes, documents, federations, authentication, and search operations.

Index Management

Tool Name	Description
create_index	Create a new index with the specified schema. This will empty the index if it already exists.
delete_index	Delete an index and all its documents permanently.
get_all_index_stats	Get document counts and statistics for all indexes.
get_index_schema	Get the schema definition for a specific index.
get_index_stats	Get statistics and metadata for a specific index (document count, etc.).
list_all_indexes	Get a list of all indexes in the Searchcraft instance.
patch_index	Make partial configuration changes to an index schema (search_fields, weight_multipliers, etc.).
update_index	Replace the entire contents of an existing index with a new schema definition.

Document Management

Tool Name	Description
add_documents	Add one or multiple documents to an index. Documents should be provided as an array of JSON objects.
delete_all_documents	Delete all documents from an index. The index will continue to exist after all documents are deleted.
delete_document_by_id	Delete a single document from an index by its internal Searchcraft ID (_id).
delete_documents_by_field	Delete one or several documents from an index by field term match (e.g., {id: 'xyz'} or {title: 'foo'}).
delete_documents_by_query	Delete one or several documents from an index by query match.
get_document_by_id	Get a single document from an index by its internal Searchcraft ID (_id).

Federation Management

Tool Name	Description
create_federation	Create or update a federation with the specified configuration.
delete_federation	Delete a federation permanently.
get_federation_details	Get detailed information for a specific federation.
get_federation_stats	Get document counts per index for a federation as well as the total document count.
get_organization_federations	Get a list of all federations for a specific organization.
list_all_federations	Get a list of all federations in the Searchcraft instance.
update_federation	Replace the current federation entity with an updated one.

Authentication & Key Management

Tool Name	Description
create_key	Create a new authentication key with specified permissions and access controls.
delete_all_keys	Delete all authentication keys on the Searchcraft cluster. Use with extreme caution!
delete_key	Delete a specific authentication key permanently.
get_application_keys	Get a list of all authentication keys associated with a specific application.
get_federation_keys	Get a list of all authentication keys associated with a specific federation.
get_key_details	Get detailed information for a specific authentication key.
get_organization_keys	Get a list of all authentication keys associated with a specific organization.
list_all_keys	Get a list of all authentication keys on the Searchcraft cluster.
update_key	Update an existing authentication key with new configuration.

Stopwords Management

Tool Name	Description
add_stopwords	Add custom stopwords to an index. These are added on top of the default language-specific dictionary.
delete_all_stopwords	Delete all custom stopwords from an index. This only affects custom stopwords, not the default language dictionary.
delete_stopwords	Delete specific custom stopwords from an index. This only affects custom stopwords, not the default language dictionary.
get_index_stopwords	Get all stopwords for an index, including both default language dictionary and custom stopwords.

Synonyms Management

Tool Name	Description
add_synonyms	Add synonyms to an index. Synonyms only work with fuzzy queries, not exact match queries.
delete_all_synonyms	Delete all synonyms from an index.
delete_synonyms	Delete specific synonyms from an index by their keys.
get_index_synonyms	Get all synonyms defined for an index.

Search & Analytics

Tool Name	Description
get_measure_conversion	Get measurement conversion data with optional filtering and aggregation parameters. *requires Clickhouse if running locally
get_measure_summary	Get measurement summary data with optional filtering and aggregation parameters. *requires Clickhouse if running locally
get_search_results	Performs a search query using the Searchcraft API with support for fuzzy/exact matching, facets, and date ranges.
get_prelim_search_data	Get schema fields and facet information for a search index to understand available fields for constructing queries.
get_searchcraft_status	Get the current status of the Searchcraft search service.

Import Tools

These tools provide workflows for importing JSON data and automatically generating Searchcraft schemas. Perfect for quickly setting up new indexes from existing data sources.

Tool Name	Description
analyze_json_from_file	Read JSON data from a local file and analyze its structure to understand field types and patterns for Searchcraft index schema generation.
analyze_json_from_url	Fetch JSON data from a URL and analyze its structure to understand field types and patterns for Searchcraft index schema generation.
generate_searchcraft_schema	Generate a complete Searchcraft index schema from analyzed JSON structure, with customizable options for search fields, weights, and other index settings.
create_index_from_json	Complete workflow to create a Searchcraft index from JSON data. Fetches JSON from URL or file, analyzes structure, generates schema, creates the index, and adds all documents in one step.

Import Tools Workflow

The import tools are designed to work together in a streamlined workflow:

Analyze → Use analyze_json_from_file or analyze_json_from_url to examine your JSON data structure
Generate → Use generate_searchcraft_schema to create a customized Searchcraft schema from the analysis
Create → Use the Engine API create_index tool to create the index with your generated schema
Import → Use add_documents to populate your new index with data

Or use the all-in-one approach:

One-Step → Use create_index_from_json to analyze, generate schema, create the index, and import all documents in one command

App Generation Tools

These tools create complete, ready-to-run search applications from your JSON data, perfect for prototyping and demos.

Tool Name	Description
create_vite_app	Creates a complete Vite + React search application from JSON data. Analyzes your data structure, generates optimized search templates, and creates a fully functional web app with Searchcraft integration.

App Generation Workflow

The app generation tools provide an end-to-end solution for creating search applications:

Data Analysis → Automatically analyzes your JSON structure to understand field types and content
Template Generation → Creates optimized search result templates based on your data fields
App Creation → Clones and configures a complete Vite + React application
Environment Setup → Configures Searchcraft connection settings
Ready to Run → Provides a fully functional search app you can immediately start and customize

Detailed Tool Usage

Using create_index_from_json

The create_index_from_json tool provides a complete workflow to create a Searchcraft index from JSON data in a single command. This is perfect for quickly setting up search indexes from existing datasets. Note, if you know the language of the data you are importing you should specify it with the language parameter (use the ISO 639-1 two letter code for the language)

Parameters

Parameter	Type	Required	Description
`source`	`"url"` or `"file"`	✅	Whether to fetch data from a URL or read from a local file
`path`	`string`	✅	URL or file path to the JSON data
`index_name`	`string`	✅	Name for the new Searchcraft index
`sample_size`	`number`	❌	Number of items to analyze for schema generation (default: 10)
`search_fields`	`string[]`	❌	Override automatically detected search fields
`weight_multipliers`	`object`	❌	Custom field weights for search relevance (0.0-10.0)
`language`	`string`	❌	Language code for the index (e.g., "en", "es")
`auto_commit_delay`	`number`	❌	Auto commit delay in seconds
`exclude_stop_words`	`boolean`	❌	Whether to exclude stop words from search
`time_decay_field`	`string`	❌	Field name for time-based relevance decay

Example Usage

From a URL:

{ "source": "url", "path": "https://api.example.com/products.json", "index_name": "products", "sample_size": 50, "search_fields": ["title", "description", "category"], "weight_multipliers": { "title": 2.0, "description": 1.0, "category": 1.5 } }

From a local file:

{ "source": "file", "path": "/path/to/data.json", "index_name": "my_data", "language": "en" }

What it does

Fetches/Reads Data → Downloads from URL or reads from local file
Analyzes Structure → Examines JSON to understand field types and patterns
Generates Schema → Creates optimized Searchcraft index schema
Creates Index → Sets up the index in your Searchcraft cluster
Imports Documents → Adds all JSON data as searchable documents
Returns Summary → Provides detailed information about what was created

Expected JSON Format

The tool works with various JSON structures:

Array of objects: [{...}, {...}, ...]
Object with array property: {"data": [{...}, {...}], "meta": {...}}
Single object: {...} (will be treated as a single document)

The tool automatically finds the best array of objects to use for the index.

Using create_vite_app

The create_vite_app tool creates a complete, ready-to-run search application from your JSON data. It's perfect for quickly prototyping search interfaces or creating demo applications.

Parameters

Parameter	Type	Required	Description
`data_source`	`"url"` or `"file"`	✅	Whether to fetch data from a URL or read from a local file
`data_path`	`string`	✅	URL or file path to the JSON data
`app_name`	`string`	✅	Name for the generated app (used for directory name)
`VITE_ENDPOINT_URL`	`string`	✅	Your Searchcraft cluster endpoint URL
`VITE_INDEX_NAME`	`string`	✅	The Searchcraft index name to connect to
`VITE_READ_KEY`	`string`	✅	Searchcraft read key for the application
`sample_size`	`number`	❌	Number of items to analyze for template generation (default: 50)
`search_fields`	`string[]`	❌	Override automatically detected search fields
`weight_multipliers`	`object`	❌	Custom field weights for search relevance (0.0-10.0)

Example Usage

If you saw the prompt earlier in the documentation you can easily use the create_vite_app tool with natural language. However, you want finer grain control you can use the tool with JSON parameters.

Creating a product search app:

{ "data_source": "url", "data_path": "https://api.example.com/products.json", "app_name": "product-search", "VITE_ENDPOINT_URL": "https://your-cluster.searchcraft.io", "VITE_INDEX_NAME": "products", "VITE_READ_KEY": "your_read_key_here", "sample_size": 100, "search_fields": ["title", "description", "brand"], "weight_multipliers": { "title": 2.5, "description": 1.0, "brand": 1.8 } }

Creating a blog search app from local data:

{ "data_source": "file", "data_path": "/path/to/blog-posts.json", "app_name": "blog-search", "VITE_ENDPOINT_URL": "https://your-cluster.searchcraft.io", "VITE_INDEX_NAME": "blog_posts", "VITE_READ_KEY": "your_read_key_here" }

What it does

Analyzes Data Structure → Examines your JSON to understand field types and content patterns
Generates Search Templates → Creates optimized result display templates based on your data
Clones Vite Template → Downloads the official Searchcraft Vite + React template
Installs Dependencies → Sets up all required npm packages
Configures Environment → Creates .env file with your Searchcraft settings
Customizes Templates → Generates dynamic search result components
Updates App Code → Modifies the main app with your specific branding and configuration

Generated App Features

The created application includes:

React + Vite → Modern, fast development setup
Searchcraft SDK Integration → Full search functionality out of the box
Responsive Design → Works on desktop and mobile devices
Auto-generated Templates → Smart result display based on your data structure
Environment Configuration → Easy setup for different environments
Development Server → Hot reload for rapid customization

Template Generation Logic

The tool intelligently analyzes your data to create optimal search result templates:

Title Field Detection → Finds the best field to use as the main title
Description Field Detection → Identifies descriptive text fields
Image Field Detection → Locates image URLs for visual results
Date Field Detection → Finds timestamp fields for temporal sorting
Additional Fields → Includes other relevant text fields for comprehensive results

Next Steps After Creation

Once the app is created, you can:

Start Vite Server:
cd apps/your-app-name yarn dev
Customize Styling → Modify CSS and components to match your brand
Add Features → Extend with filters, facets, or advanced search options
Deploy → Build and deploy to your preferred hosting platform

Prerequisites

Existing Searchcraft Index → The index specified in VITE_INDEX_NAME should already exist
Valid Read Key → The VITE_READ_KEY must have read permissions for the index
Git Available → The tool uses git to clone the template repository
Node.js & Yarn → Required for dependency installation

Complete Workflow: From JSON to Search App

Here's how to use both tools together to go from raw JSON data to a fully functional search application:

Option 1: Two-Step Process (Recommended for Production)

Step 1: Create the Searchcraft Index

{ "source": "url", "path": "https://api.example.com/products.json", "index_name": "products", "sample_size": 100, "search_fields": ["title", "description", "category", "brand"], "weight_multipliers": { "title": 2.5, "description": 1.0, "category": 1.8, "brand": 1.5 }, "language": "en" }

Step 2: Create the Search Application

{ "data_source": "url", "data_path": "https://api.example.com/products.json", "app_name": "product-search-app", "VITE_ENDPOINT_URL": "https://your-cluster.searchcraft.io", "VITE_INDEX_NAME": "products", "VITE_READ_KEY": "your_read_key_here", "sample_size": 100, "search_fields": ["title", "description", "category", "brand"], "weight_multipliers": { "title": 2.5, "description": 1.0, "category": 1.8, "brand": 1.5 } }

Option 2: App-Only Process (For Existing Indexes)

If you already have a Searchcraft index set up, you can jump straight to creating the app:

{ "data_source": "url", "data_path": "https://api.example.com/products.json", "app_name": "my-search-app", "VITE_ENDPOINT_URL": "https://your-cluster.searchcraft.io", "VITE_INDEX_NAME": "existing_index", "VITE_READ_KEY": "your_read_key_here" }

Benefits of the Two-Step Approach

Index Optimization → Fine-tune your search index separately from the UI
Multiple Apps → Create different search interfaces for the same data
Production Ready → Better separation of concerns for production deployments
Easier Debugging → Test search functionality independently of the UI

Getting Started

Environment Variables

Create .env file at the project's root and fill in the values:

# Server Config USER_AGENT=searchcraft-mcp-server/<project-version> DEBUG=true PORT=3100 # Searchcraft Config ENDPOINT_URL= # The endpoint url of your Searchcraft Cluster ADMIN_KEY= # The admin key (super user key) of your Searchcraft Cluster when running locally.

.env sample

Remote Usage

If you have already created an index through Vektron on Searchcraft Cloud you may use the write key for the index you are trying to access and use the MCP server for API operations that don't require admin privileges. IMPORTANT: If you use the MCP server with a write key it should NOT be publicly exposed to the internet. Write keys are intended to be secured and by running an MCP server any user with access to the MCP server will be able to write to the index or delete data.

Installation & Setup

Make sure your environment has the correct version of node selected.

nvm use

Install dependencies with yarn

yarn

Build the server

yarn build

This creates two server versions:

dist/server.js - HTTP server for testing and remote deployment
dist/stdio-server.js - stdio server for Claude Desktop

Usage

Option 1: Claude Desktop (stdio) - Recommended

For local use with Claude Desktop, use the stdio version which provides better performance and reliability.

claude_desktop_config.json

{ "mcpServers": { "searchcraft": { "command": "node", "args": [ "/path/to/searchcraft-mcp-server/dist/stdio-server.js" ] } } }

The claude desktop config file can be found at:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

If the file doesn't exist, create it.

Option 2: Claude Code

For use with Claude Code, use the CLI to configure the MCP server:

Basic setup:

# Add the Searchcraft MCP server to Claude Code claude mcp add searchcraft -- node /path/to/searchcraft-mcp-server/dist/stdio-server.js

With environment variables:

# Add with your Searchcraft cluster configuration claude mcp add searchcraft \ --env ENDPOINT_URL=https://your-cluster.searchcraft.io \ --env ADMIN_KEY=your_admin_key_here \ -- node /path/to/searchcraft-mcp-server/dist/stdio-server.js

Configuration scopes:

--scope local (default): Available only to you in the current project
--scope project: Shared with team via .mcp.json file (recommended for teams)
--scope user: Available to you across all projects

Managing servers:

# List configured servers claude mcp list # Check server status /mcp # Remove server claude mcp remove searchcraft

Option 3: Open WebUI (via Pipelines)

Open WebUI supports MCP servers through its Pipelines framework. This requires creating a custom pipeline that bridges your MCP server to Open WebUI.

Step 1: Start the Searchcraft MCP HTTP server

yarn start # Starts HTTP server on port 3100

Step 2: Create an MCP Pipeline for Open WebUI

Create a file called searchcraft_mcp_pipeline.py:

""" title: Searchcraft MCP Pipeline author: Searchcraft Team version: 1.0.0 license: Apache-2.0 description: A pipeline that integrates Searchcraft MCP server with Open WebUI requirements: requests """ import requests import json from typing import List, Union, Generator, Iterator from pydantic import BaseModel class Pipeline: class Valves(BaseModel): MCP_SERVER_URL: str = "http://localhost:3100/mcp" ENDPOINT_URL: str = "" ADMIN_KEY: str = "" def __init__(self): self.name = "Searchcraft MCP Pipeline" self.valves = self.Valves() async def on_startup(self): print(f"on_startup:{__name__}") async def on_shutdown(self): print(f"on_shutdown:{__name__}") def pipe( self, user_message: str, model_id: str, messages: List[dict], body: dict ) -> Union[str, Generator, Iterator]: # This pipeline acts as a bridge between Open WebUI and your MCP server # You can customize this to handle specific Searchcraft operations # Example: If user mentions search operations, route to MCP server if any(keyword in user_message.lower() for keyword in ['search', 'index', 'document', 'searchcraft']): try: # Initialize MCP session init_payload = { "jsonrpc": "2.0", "id": 1, "method": "initialize", "params": { "protocolVersion": "2025-06-18", "capabilities": {}, "clientInfo": {"name": "open-webui-pipeline", "version": "1.0.0"} } } response = requests.post(self.valves.MCP_SERVER_URL, json=init_payload) if response.status_code == 200: # Add context about available Searchcraft tools enhanced_message = f""" {user_message} [Available Searchcraft MCP Tools: create_index, delete_index, add_documents, get_search_results, list_all_indexes, get_index_stats, create_key, delete_key, and 20+ more tools for managing Searchcraft clusters] """ return enhanced_message except Exception as e: print(f"MCP connection error: {e}") return user_message

Step 3: Install the Pipeline in Open WebUI

Via Admin Panel:
- Go to Admin Settings → Pipelines
- Click "Add Pipeline"
- Paste the pipeline code above
- Configure the valves with your Searchcraft settings:
  - MCP_SERVER_URL: http://localhost:3100/mcp
  - ENDPOINT_URL: Your Searchcraft cluster URL
  - ADMIN_KEY: Your Searchcraft admin key
Via Docker Environment:
# Save the pipeline to a file and mount it docker run -d -p 3000:8080 \ -v open-webui:/app/backend/data \ -v ./searchcraft_mcp_pipeline.py:/app/backend/data/pipelines/searchcraft_mcp_pipeline.py \ --name open-webui \ ghcr.io/open-webui/open-webui:main

Step 4: Configure Open WebUI to use Pipelines

Start Open WebUI with Pipelines support:
# Using Docker Compose (recommended) services: openwebui: image: ghcr.io/open-webui/open-webui:main ports: - "3000:8080" volumes: - open-webui:/app/backend/data environment: - OPENAI_API_BASE_URL=http://pipelines:9099 - OPENAI_API_KEY=0p3n-w3bu! pipelines: image: ghcr.io/open-webui/pipelines:main volumes: - pipelines:/app/pipelines environment: - PIPELINES_API_KEY=0p3n-w3bu!
In Open WebUI Settings → Connections:
- Set OpenAI API URL to your Pipelines instance
- Enable the Searchcraft MCP Pipeline

Option 4: HTTP Server (for testing/remote deployment)

Start the HTTP server for testing, debugging, or remote deployment:

yarn start # Starts HTTP server on port 3100

For Claude Desktop with HTTP server, you'll need mcp-remote:

claude_desktop_config.json

{ "mcpServers": { "searchcraft": { "command": "npx", "args": [ "mcp-remote", "http://localhost:3100/mcp" ] } } }

Available Scripts

# Development yarn dev # Watch HTTP server yarn dev:stdio # Watch stdio server # Production yarn start # Start HTTP server yarn start:stdio # Start stdio server # Testing yarn inspect # Launch MCP inspector yarn claude-logs # View Claude Desktop logs

stdio vs HTTP: Which to Choose?

Feature	stdio (Recommended)	HTTP
Performance	✅ Direct IPC, lower latency	⚠️ HTTP overhead
Security	✅ No exposed ports	⚠️ Network port required
Simplicity	✅ No port management	⚠️ Port conflicts possible
Claude Desktop	✅ Native support	⚠️ Requires mcp-remote
Claude Code	✅ Native support	✅ Native support
Open WebUI	❌ Not supported	✅ Via Pipelines framework
Remote Access	❌ Local only	✅ Can deploy remotely
Testing	⚠️ Requires MCP tools	✅ Easy with curl/Postman
Multiple Clients	❌ One client at a time	✅ Multiple concurrent clients

Use stdio when:

Using Claude Desktop or Claude Code locally
You want the best performance
You prefer simplicity

Use HTTP when:

You need remote access
You want easy testing/debugging
You need multiple concurrent clients
You're deploying to a server
Using Open WebUI or other web-based interfaces

Debugging

Claude Desktop Logs

To view Claude Desktop's logs for debugging MCP connections:

yarn claude-logs

Testing with MCP Inspector

The MCP Inspector allows you to test your server tools interactively.

For stdio server (recommended):

yarn inspect

Choose Transport Type: stdio
Command: node dist/stdio-server.js

For HTTP server:

yarn start # Start HTTP server first yarn inspect

Choose Transport Type: Streamable HTTP
URL: http://localhost:3100/mcp

Manual Testing

Test HTTP server:

# Health check curl http://localhost:3100/health # Test MCP endpoint curl -X POST http://localhost:3100/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"test","version":"1.0.0"}}}'

Test stdio server:

echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"test","version":"1.0.0"}}}' | node dist/stdio-server.js

Resources

Issues and Feature Requests

Visit https://github.com/searchcraft-inc/searchcraft-issues

License

Licensed under the Apache 2.0 License.

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

An MCP server that enables AI assistants like Claude Desktop to search and retrieve information from custom search indexes created with Searchcraft.

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Sample Prompts

Available Tools

Engine API Tools

Index Management

Document Management

Federation Management

Authentication & Key Management

Stopwords Management

Synonyms Management

Search & Analytics

Import Tools

Import Tools Workflow

App Generation Tools

App Generation Workflow

Detailed Tool Usage

Using create_index_from_json

Parameters

Example Usage

What it does

Expected JSON Format

Using create_vite_app

Parameters

Example Usage

What it does

Generated App Features

Template Generation Logic

Next Steps After Creation

Prerequisites

Complete Workflow: From JSON to Search App

Option 1: Two-Step Process (Recommended for Production)

Option 2: App-Only Process (For Existing Indexes)

Benefits of the Two-Step Approach

Getting Started

Environment Variables

Remote Usage

Installation & Setup

Usage

Option 1: Claude Desktop (stdio) - Recommended

Option 2: Claude Code

Option 3: Open WebUI (via Pipelines)

Option 4: HTTP Server (for testing/remote deployment)

Available Scripts

stdio vs HTTP: Which to Choose?

Debugging

Claude Desktop Logs

Testing with MCP Inspector

Manual Testing

Resources

Issues and Feature Requests

License

Related MCP Servers

Search MCP Server

Terminal MCP Server

Claude AI Documentation Assistant

sysauto Ask MCP Server

New MCP Servers

MCP directory API