Opensearch MCP Server
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Provides a Model Context Protocol interface that lets AI assistants query, manage, and analyze OpenSearch clusters through both stdio and streaming transports.
Opensearch MCP Server Overview
What is Opensearch MCP Server about?
Enables AI assistants and large language models to interact with OpenSearch clusters via a standardized protocol, exposing common search, mapping, health, and shard operations as callable tools.
How to use Opensearch MCP Server?
- Install the package from PyPI:
pip install opensearch-mcp-server-py - After installation a console entry point is available (e.g.,
opensearch-mcp-server). Run it directly or wrap it in a service manager. - Configure authentication through basic auth or IAM roles using environment variables such as
OPENSEARCH_USERNAME,OPENSEARCH_PASSWORD, orAWS_REGION. - Enable or disable tool categories via environment variables, e.g.,
OPENSEARCH_DISABLED_CATEGORIES=core_tools. - Connect AI assistants (Claude Desktop, LangChain, etc.) to the server using the MCP transport (stdio, SSE, or streamable HTTP).
Key Features
- Seamless integration with AI assistants and LLMs through MCP.
- Supports stdio, Server‑Sent Events, and Streamable HTTP transports.
- Core toolset enabled by default (list indices, mapping, search, shard info, cluster health, count, explain, multi‑search).
- Additional diagnostic tools available on demand (cluster state, segments, node info, allocation, long‑running tasks, etc.).
- Flexible authentication: basic auth or AWS IAM roles.
- Simple environment‑based configuration for tool categories and server options.
Use Cases
- Building AI‑driven chat interfaces that can query OpenSearch indexes on the fly.
- Automating cluster health checks and reporting via LLM‑generated summaries.
- Enabling LangChain agents to perform search, retrieve, and explain operations without custom code.
- Debugging and monitoring OpenSearch clusters using AI assistants that can invoke diagnostic tools.
- Rapid prototyping of data‑exploration bots that need direct access to search results and index metadata.
FAQ
Q: How do I install the server?
A: Use pip install opensearch-mcp-server-py and then run the provided entry point.
Q: Which transport should I choose? A: For command‑line integration use stdio; for web‑based agents use SSE or streamable HTTP.
Q: How can I disable specific tools?
A: Set OPENSEARCH_DISABLED_CATEGORIES (e.g., core_tools) or use a custom tool filter as described in the User Guide.
Q: Do I need an AWS account? A: Only if you want IAM‑based authentication; otherwise basic auth with username/password works.
Q: Can I add my own tools? A: Yes—follow the developer guide to implement additional MCP tools and register them under a new category.
Opensearch MCP Server's README
- OpenSearch MCP Server
- Installing opensearch-mcp-server-py
- Available tools
- User Guide
- Contributing
- Code of Conduct
- License
- Copyright
OpenSearch MCP Server
opensearch-mcp-server-py is a Model Context Protocol (MCP) server for OpenSearch that enables AI assistants to interact with OpenSearch clusters. It provides a standardized interface for AI models to perform operations like searching indices, retrieving mappings, and managing shards through both stdio and streaming (SSE/Streamable HTTP) protocols.
Key features:
- Seamless integration with AI assistants and LLMs through the MCP protocol
- Support for both stdio and streaming server transports (SSE and Streamable HTTP)
- Built-in tools for common OpenSearch operations
- Easy integration with Claude Desktop and LangChain
- Secure authentication using basic auth or IAM roles
Installing opensearch-mcp-server-py
Opensearch-mcp-server-py can be installed from PyPI via pip:
pip install opensearch-mcp-server-py
Available Tools
By default, only core tools are enabled to provide essential OpenSearch functionality:
Core Tools (Enabled by Default)
Core tools are grouped under the core_tools category and can be disabled at once using OPENSEARCH_DISABLED_CATEGORIES=core_tools. Avoid creating custom categories with this name as they will override the built-in category.
- ListIndexTool: Lists all indices in OpenSearch with full information including docs.count, docs.deleted, store.size, etc. If an index parameter is provided, returns detailed information about that specific index.
- IndexMappingTool: Retrieves index mapping and setting information for an index in OpenSearch.
- SearchIndexTool: Searches an index using a query written in query domain-specific language (DSL) in OpenSearch.
- GetShardsTool: Gets information about shards in OpenSearch.
- ClusterHealthTool: Returns basic information about the health of the cluster.
- CountTool: Returns number of documents matching a query.
- ExplainTool: Returns information about why a specific document matches (or doesn't match) a query.
- MsearchTool: Allows to execute several search operations in one request.
Additional Tools (Disabled by Default)
The following tools are available but disabled by default. To enable them, see the Tool Filter section in the User Guide.
- GetClusterStateTool: Gets the current state of the cluster including node information, index settings, and more.
- GetSegmentsTool: Gets information about Lucene segments in indices, including memory usage, document counts, and segment sizes.
- CatNodesTool: Gets information about nodes in the OpenSearch cluster, including system metrics like CPU usage, memory, disk space, and node roles.
- GetNodesTool: Gets detailed information about nodes in the OpenSearch cluster, including static information like host system details, JVM info, processor type, node settings, thread pools, installed plugins, and more.
- GetIndexInfoTool: Gets detailed information about an index including mappings, settings, and aliases. Supports wildcards in index names.
- GetIndexStatsTool: Gets statistics about an index including document count, store size, indexing and search performance metrics.
- GetQueryInsightsTool: Gets query insights from the /_insights/top_queries endpoint, showing information about query patterns and performance.
- GetNodesHotThreadsTool: Gets information about hot threads in the cluster nodes from the /_nodes/hot_threads endpoint.
- GetAllocationTool: Gets information about shard allocation across nodes in the cluster from the /_cat/allocation endpoint.
- GetLongRunningTasksTool: Gets information about long-running tasks in the cluster, sorted by running time in descending order.
Tool Parameters
-
ListIndexTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(optional): The name of the index to get detailed information for. If provided, returns detailed information about this specific index instead of listing all indices.
-
IndexMappingTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(required): The name of the index to retrieve mappings for
-
SearchIndexTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(required): The name of the index to search inquery(required): The search query in OpenSearch Query DSL format
-
GetShardsTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(required): The name of the index to get shard information for
-
ClusterHealthTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(optional): Limit health reporting to a specific index
-
CountTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(optional): The name of the index to count documents inbody(optional): Query in JSON format to filter documents
-
ExplainTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(required): The name of the index to retrieve the document fromid(required): The document ID to explainbody(required): Query in JSON format to explain against the document
-
MsearchTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(optional): Default index to search inbody(required): Multi-search request body in NDJSON format
-
GetClusterStateTool
opensearch_url(optional): The OpenSearch cluster URL to connect tometric(optional): Limit the information returned to the specified metrics. Options include: _all, blocks, metadata, nodes, routing_table, routing_nodes, master_node, versionindex(optional): Limit the information returned to the specified indices
-
GetSegmentsTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(optional): Limit the information returned to the specified indices. If not provided, returns segments for all indices
-
CatNodesTool
opensearch_url(optional): The OpenSearch cluster URL to connect tometrics(optional): A comma-separated list of metrics to display. Available metrics include: id, name, ip, port, role, master, heap.percent, ram.percent, cpu, load_1m, load_5m, load_15m, disk.total, disk.used, disk.avail, disk.used_percent
-
GetNodesTool
opensearch_url(optional): The OpenSearch cluster URL to connect tonode_id(optional): A comma-separated list of node IDs or names to limit the returned information. Supports node filters like _local, _master, master:true, data:false, etc. Defaults to _all.metric(optional): A comma-separated list of metric groups to include in the response. Options include: settings, os, process, jvm, thread_pool, transport, http, plugins, ingest, aggregations, indices. Defaults to all metrics.
-
GetIndexInfoTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(required): The name of the index to get detailed information for. Wildcards are supported.
-
GetIndexStatsTool
opensearch_url(optional): The OpenSearch cluster URL to connect toindex(required): The name of the index to get statistics for. Wildcards are supported.metric(optional): Limit the information returned to the specified metrics. Options include: _all, completion, docs, fielddata, flush, get, indexing, merge, query_cache, refresh, request_cache, search, segments, store, warmer, bulk
-
GetQueryInsightsTool
opensearch_url(optional): The OpenSearch cluster URL to connect to
-
GetNodesHotThreadsTool
opensearch_url(optional): The OpenSearch cluster URL to connect to
-
GetAllocationTool
opensearch_url(optional): The OpenSearch cluster URL to connect to
-
GetLongRunningTasksTool
opensearch_url(optional): The OpenSearch cluster URL to connect tolimit(optional): The maximum number of tasks to return. Default is 10.
More tools coming soon. Click here
User Guide
For detailed usage instructions, configuration options, and examples, please see the User Guide.
Contributing
Interested in contributing? Check out our:
- Development Guide - Setup your development environment
- Contributing Guidelines - Learn how to contribute
Code of Conduct
This project has adopted the Amazon Open Source Code of Conduct. For more information see the Code of Conduct FAQ, or contact opensource-codeofconduct@amazon.com with any additional questions or comments.
License
This project is licensed under the Apache v2.0 License.
Copyright
Copyright 2020-2021 Amazon.com, Inc. or its affiliates. All Rights Reserved.
Opensearch MCP Server Reviews
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Opensearch MCP Server's Information
- Author
- opensearch-project
- Category
- AI Services
- Language
- Python
- License
- Apache License 2.0
- Stars
- 53
- Updated
- about 1 month ago
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