octodet-elasticsearch-mcp
Read/write Elasticsearch mcp server with many tools
Tools
list_indices
List all available Elasticsearch indices with detailed information
get_mappings
Get field mappings for a specific Elasticsearch index
search
Perform an Elasticsearch search with the provided query DSL and highlighting
get_cluster_health
Get health information about the Elasticsearch cluster
get_shards
Get shard information for all or specific indices
add_document
Add a new document to a specific Elasticsearch index
update_document
Update an existing document in a specific Elasticsearch index
delete_document
Delete a document from a specific Elasticsearch index
update_by_query
Update documents in an Elasticsearch index based on a query
delete_by_query
Delete documents in an Elasticsearch index based on a query
bulk
Perform multiple document operations (create, update, delete) in a single API call
create_index
Create a new Elasticsearch index with optional settings and mappings
delete_index
Delete an Elasticsearch index
count_documents
Count documents in an index, optionally filtered by a query
get_templates
Get index templates from Elasticsearch
get_aliases
Get index aliases from Elasticsearch
README
Octodet Elasticsearch MCP Server
A Model Context Protocol (MCP) server for Elasticsearch operations, providing a comprehensive set of tools for interacting with Elasticsearch clusters through the standardized Model Context Protocol. This server enables LLM-powered applications to search, update, and manage Elasticsearch data.
<a href="https://glama.ai/mcp/servers/@Octodet/elasticsearch-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@Octodet/elasticsearch-mcp/badge" alt="octodet-elasticsearch-mcp MCP server" /> </a>
Features
- Complete Elasticsearch Operations: Full CRUD operations for documents and indices
- Bulk Operations: Process multiple operations in a single API call
- Query-Based Updates/Deletes: Modify or remove documents based on queries
- Cluster Management: Monitor health, shards, and templates
- Advanced Search: Full support for Elasticsearch DSL queries with highlighting
Installation
As an NPM Package
Install the package globally:
npm install -g @octodet/elasticsearch-mcp
Or use it directly with npx:
npx @octodet/elasticsearch-mcp
From Source
- Clone this repository
- Install dependencies:
npm install
- Build the server:
npm run build
Integration with MCP Clients
VS Code Integration
Add the following configuration to your VS Code settings.json to integrate with the VS Code MCP extension:
"mcp.servers": {
"elasticsearch": {
"command": "npx",
"args": [
"-y", "@octodet/elasticsearch-mcp"
],
"env": {
"ES_URL": "http://localhost:9200",
"ES_API_KEY": "your_api_key",
"ES_VERSION": "8"
}
}
}
Claude Desktop Integration
Configure in your Claude Desktop configuration file:
{
"mcpServers": {
"elasticsearch": {
"command": "npx",
"args": ["-y", "@octodet/elasticsearch-mcp"],
"env": {
"ES_URL": "http://localhost:9200",
"ES_API_KEY": "your_api_key",
"ES_VERSION": "8"
}
}
}
}
For Local Development
If you're developing the MCP server locally, you can configure the clients to use your local build:
{
"mcpServers": {
"elasticsearch": {
"command": "node",
"args": ["path/to/build/index.js"],
"env": {
"ES_URL": "http://localhost:9200",
"ES_API_KEY": "your_api_key",
"ES_VERSION": "8"
}
}
}
}
Configuration
The server uses the following environment variables for configuration:
| Variable | Description | Default |
|---|---|---|
| ES_URL | Elasticsearch server URL | http://localhost:9200 |
| ES_API_KEY | API key for authentication | |
| ES_USERNAME | Username for authentication | |
| ES_PASSWORD | Password for authentication | |
| ES_CA_CERT | Path to custom CA certificate | |
| ES_VERSION | Elasticsearch version (8 or 9) | 8 |
| ES_SSL_SKIP_VERIFY | Skip SSL verification | false |
| ES_PATH_PREFIX | Path prefix for Elasticsearch |
Tools
The server provides 16 MCP tools for Elasticsearch operations. Each tool is documented with its required and optional parameters:
1. List Indices
List all available Elasticsearch indices with detailed information.
Parameters:
indexPattern(optional, string): Pattern to filter indices (e.g., "logs-", "my-index-")
Example:
{
"indexPattern": "logs-*"
}
2. Get Mappings
Get field mappings for a specific Elasticsearch index.
Parameters:
index(required, string): The name of the index to get mappings for
Example:
{
"index": "my-index"
}
3. Search
Perform an Elasticsearch search with the provided query DSL and highlighting.
Parameters:
index(required, string): The index or indices to search in (supports comma-separated values)queryBody(required, object): The Elasticsearch query DSL bodyhighlight(optional, boolean): Enable search result highlighting (default: true)
Example:
{
"index": "my-index",
"queryBody": {
"query": {
"match": {
"content": "search term"
}
},
"size": 10,
"from": 0,
"sort": [{ "_score": { "order": "desc" } }]
},
"highlight": true
}
4. Get Cluster Health
Get health information about the Elasticsearch cluster.
Parameters:
- None required
Example:
{}
5. Get Shards
Get shard information for all or specific indices.
Parameters:
index(optional, string): Specific index to get shard information for. If omitted, returns shards for all indices
Example:
{
"index": "my-index"
}
6. Add Document
Add a new document to a specific Elasticsearch index.
Parameters:
index(required, string): The index to add the document todocument(required, object): The document content to addid(optional, string): Document ID. If omitted, Elasticsearch will generate one automatically
Example:
{
"index": "my-index",
"id": "doc1",
"document": {
"title": "My Document",
"content": "Document content here",
"timestamp": "2025-06-23T10:30:00Z",
"tags": ["important", "draft"]
}
}
7. Update Document
Update an existing document in a specific Elasticsearch index.
Parameters:
index(required, string): The index containing the documentid(required, string): The ID of the document to updatedocument(required, object): The partial document with fields to update
Example:
{
"index": "my-index",
"id": "doc1",
"document": {
"title": "Updated Document Title",
"last_modified": "2025-06-23T10:30:00Z"
}
}
8. Delete Document
Delete a document from a specific Elasticsearch index.
Parameters:
index(required, string): The index containing the documentid(required, string): The ID of the document to delete
Example:
{
"index": "my-index",
"id": "doc1"
}
9. Update By Query
Update documents in an Elasticsearch index based on a query.
Parameters:
index(required, string): The index to update documents inquery(required, object): Elasticsearch query to match documents for updatescript(required, object): Script to execute for updating matched documentsconflicts(optional, string): How to handle version conflicts ("abort" or "proceed", default: "abort")refresh(optional, boolean): Whether to refresh the index after the operation (default: false)
Example:
{
"index": "my-index",
"query": {
"term": {
"status": "active"
}
},
"script": {
"source": "ctx._source.status = params.newStatus; ctx._source.updated_at = params.timestamp",
"params": {
"newStatus": "inactive",
"timestamp": "2025-06-23T10:30:00Z"
}
},
"conflicts": "proceed",
"refresh": true
}
10. Delete By Query
Delete documents in an Elasticsearch index based on a query.
Parameters:
index(required, string): The index to delete documents fromquery(required, object): Elasticsearch query to match documents for deletionconflicts(optional, string): How to handle version conflicts ("abort" or "proceed", default: "abort")refresh(optional, boolean): Whether to refresh the index after the operation (default: false)
Example:
{
"index": "my-index",
"query": {
"range": {
"created_date": {
"lt": "2025-01-01"
}
}
},
"conflicts": "proceed",
"refresh": true
}
11. Bulk Operations
Perform multiple document operations in a single API call for better performance.
Parameters:
operations(required, array): Array of operation objects, each containing:action(required, string): The operation type ("index", "create", "update", or "delete")index(required, string): The index for this operationid(optional, string): Document ID (required for update/delete, optional for index/create)document(conditional, object): Document content (required for index/create/update operations)
Example:
{
"operations": [
{
"action": "index",
"index": "my-index",
"id": "doc1",
"document": { "title": "Document 1", "content": "Content here" }
},
{
"action": "update",
"index": "my-index",
"id": "doc2",
"document": { "title": "Updated Title" }
},
{
"action": "delete",
"index": "my-index",
"id": "doc3"
}
]
}
12. Create Index
Create a new Elasticsearch index with optional settings and mappings.
Parameters:
index(required, string): The name of the index to createsettings(optional, object): Index settings like number of shards, replicas, etc.mappings(optional, object): Field mappings defining how documents should be indexed
Example:
{
"index": "new-index",
"settings": {
"number_of_shards": 3,
"number_of_replicas": 1,
"analysis": {
"analyzer": {
"custom_analyzer": {
"type": "standard",
"stopwords": "_english_"
}
}
}
},
"mappings": {
"properties": {
"title": {
"type": "text",
"analyzer": "custom_analyzer"
},
"created": {
"type": "date",
"format": "yyyy-MM-dd'T'HH:mm:ss'Z'"
},
"tags": {
"type": "keyword"
}
}
}
}
13. Delete Index
Delete an Elasticsearch index permanently.
Parameters:
index(required, string): The name of the index to delete
Example:
{
"index": "my-index"
}
14. Count Documents
Count documents in an index, optionally filtered by a query.
Parameters:
index(required, string): The index to count documents inquery(optional, object): Elasticsearch query to filter documents for counting
Example:
{
"index": "my-index",
"query": {
"bool": {
"must": [
{ "term": { "status": "active" } },
{ "range": { "created_date": { "gte": "2025-01-01" } } }
]
}
}
}
15. Get Templates
Get index templates from Elasticsearch.
Parameters:
name(optional, string): Specific template name to retrieve. If omitted, returns all templates
Example:
{
"name": "logs-template"
}
16. Get Aliases
Get index aliases from Elasticsearch.
Parameters:
name(optional, string): Specific alias name to retrieve. If omitted, returns all aliases
Example:
{
"name": "logs-alias"
}
Development
Running in Development Mode
Run the server in watch mode during development:
npm run dev
Protocol Implementation
This server implements the Model Context Protocol to enable standardized communication between LLM clients and Elasticsearch. It provides a set of tools that can be invoked by MCP clients to perform various Elasticsearch operations.
Adding New Tools
To add a new tool to the server:
- Define the tool in
src/index.tsusing the MCP server's tool registration format - Implement the necessary functionality in
src/utils/elasticsearchService.ts - Update this README to document the new tool
Other MCP Clients
This server can be used with any MCP-compatible client, including:
- OpenAI's ChatGPT via MCP plugins
- Anthropic's Claude Desktop
- Claude in VS Code
- Custom applications using the MCP SDK
Programmatic Usage
You can also use the server programmatically in your Node.js applications:
import { createOctodetElasticsearchMcpServer } from "@octodet/elasticsearch-mcp";
import { CustomTransport } from "@modelcontextprotocol/sdk/server";
// Configure the Elasticsearch connection
const config = {
url: "http://localhost:9200",
apiKey: "your_api_key",
version: "8",
};
// Create and start the server
async function startServer() {
const server = await createOctodetElasticsearchMcpServer(config);
// Connect to your custom transport
const transport = new CustomTransport();
await server.connect(transport);
console.log("Elasticsearch MCP server started");
}
startServer().catch(console.error);
License
This project is licensed under the MIT License - see the LICENSE file for details.
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