opensearch-mcp-server-py

• OpenSearch MCP Server

• Installing opensearch-mcp-server-py

• Available tools

• User Guide

• Agent Memory

• 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

• Dynamic per-call connection parameters for targeting different clusters without server reconfiguration

• Easy integration with Claude Desktop and LangChain

• Secure authentication using basic auth, IAM roles, header-based auth, and OpenSearch mTLS

For detailed setup, including Kubernetes deployment and mTLS configuration, see the User Guide.

Installing opensearch-mcp-server-py

Opensearch-mcp-server-py can be installed from PyPI via pip:

pip install opensearch-mcp-server-py

Zero-Config Setup

The server can be started with no environment variables at all. Agents provide connection details dynamically on each tool call:

{
  "mcpServers": {
    "opensearch": {
      "command": "uvx",
      "args": ["opensearch-mcp-server-py"]
    }
  }
}

With this setup, agents pass opensearch_url and authentication parameters directly when calling any tool. This is useful when agents discover endpoints from a knowledge base, runbook, or SOP, or when a single agent needs to work with multiple clusters in one session. See Dynamic Connection Parameters for details.

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.

• [GenericOpenSearchApiTool]: A flexible tool that can call any OpenSearch API endpoint with custom paths, methods, query parameters, and request bodies. Reduces tool explosion by providing a single interface for all OpenSearch APIs.

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.

Agentic Memory Tools (Disabled by Default)

The following tools expose the OpenSearch Agentic Memory API — a server-side memory system built into OpenSearch itself. The OpenSearch cluster manages memory containers, sessions, and inference (LLM-based extraction of facts from conversations). These tools require OpenSearch 3.3.0 or later.

When to use: You want OpenSearch to own the full memory lifecycle — including LLM-based inference to extract facts from raw conversations, structured memory types (sessions, working, long-term, history), and server-managed namespacing. Best for production agentic pipelines where memory management should be centralized and not depend on the MCP client.

Setup: You must create a memory container in OpenSearch before using these tools (one-time admin operation requiring LLM connector and embedding model configuration). See Agentic Memory Tools in the Agent Memory Guide.

Enable with OPENSEARCH_ENABLED_CATEGORIES=agentic_memory. When memory_container_id is configured via the agentic_memory config section or OPENSEARCH_MEMORY_CONTAINER_ID environment variable, it is automatically pre-filled in all tool calls.

• CreateAgenticMemorySessionTool: Creates a new session within a memory container.

• AddAgenticMemoriesTool: Adds conversational or structured data memories to a container.

• GetAgenticMemoryTool: Retrieves a specific memory by its ID and type.

• SearchAgenticMemoryTool: Searches for memories using OpenSearch Query DSL.

• UpdateAgenticMemoryTool: Updates an existing memory (supports specific fields based on memory type).

• DeleteAgenticMemoryByIDTool: Deletes a specific memory by its ID.

• DeleteAgenticMemoryByQueryTool: Deletes multiple memories matching a query criteria.

Search Relevance Workbench Tools (Disabled by Default)

Search Relevance Workbench tools are grouped under the search_relevance category and can be enabled at once using OPENSEARCH_ENABLED_CATEGORIES=search_relevance or by adding enabled_categories: [search_relevance] or explicitly adding individual tools to their config file. See the Tool Filter section in the User Guide for additional information about how to filter tools.

• CreateSearchConfigurationTool: Creates a search configuration consisting of a name, a query body (a query in OpenSearch query domain-specific language), and the target index.

• GetSearchConfigurationTool: Retrieves a search configuration by ID.

• DeleteSearchConfigurationTool: Deletes a search configuration by ID.

• CreateQuerySetTool: Creates a query set consisting of a name, a description, and a list of queries.

• SampleQuerySetTool: Samples a query set based on UBI data with different statistical sampling techniques.

• GetQuerySetTool: Retrieves a query set by ID.

• DeleteQuerySetTool: Deletes a query set by ID.

• CreateJudgmentListTool: Creates a judgment list with judgments originating from an external process.

• CreateLLMJudgmentListTool: Creates a judgment list by using an LLM.

• CreateUBIJudgmentListTool: Creates a judgment list based on implicit feedback (User Behavior Insights data).

• GetJudgmentListTool: Retrieves a judgment list by ID.

• DeleteJudgmentListTool: Deletes a judgment list by ID.

• CreateExperimentTool: Creates a search relevance experiment. Supports PAIRWISE_COMPARISON (compares 2 search configurations), POINTWISE_EVALUATION (evaluates 1 configuration against judgment lists), and HYBRID_OPTIMIZER (optimizes 1 configuration using judgment lists).

• GetExperimentTool: Retrieves an experiment by ID.

• DeleteExperimentTool: Deletes an experiment by ID.

• SearchQuerySetsTool: Searches query sets using OpenSearch query DSL. Defaults to match_all if no query body is provided.

• SearchSearchConfigurationsTool: Searches search configurations using OpenSearch query DSL. Defaults to match_all if no query body is provided.

• SearchJudgmentsTool: Searches judgments using OpenSearch query DSL. Defaults to match_all if no query body is provided.

• SearchExperimentsTool: Searches experiments using OpenSearch query DSL. Defaults to match_all if no query body is provided.

Skills Tools (Disabled by Default)

Skills tools are grouped under the skills category and can be enabled at once using OPENSEARCH_ENABLED_CATEGORIES=skills or by adding enabled_categories: [skills] to the config file. See the Tool Filter section in the User Guide for additional information about how to filter tools.

• DataDistributionTool: Analyzes data distribution patterns and field value frequencies within OpenSearch indices. Supports both single dataset analysis and comparative analysis between two time periods to identify distribution changes.

• LogPatternAnalysisTool: Detects anomalous log patterns and sequences through comparative analysis between baseline and selection time ranges. Supports log sequence analysis with trace correlation, log pattern difference analysis, and log insights analysis for error detection.

Memory Tools (Opt-in)

Memory tools give the MCP agent itself persistent, cross-session memory backed by OpenSearch. The agent decides what to save as plain-text statements; OpenSearch stores and semantically indexes them. Enable with MEMORY_TOOLS_ENABLED=true. See the Agent Memory Guide for full setup instructions.

When to use: You want a lightweight, agent-driven memory layer that works with any MCP-compatible IDE (Kiro, Claude Code, Cursor). The agent controls what gets remembered — no LLM connectors or embedding models to configure on the OpenSearch side. Requires Amazon OpenSearch Service (managed domain 2.19+ or Serverless) for automatic semantic enrichment. See the Agent Memory Guide for full setup instructions.

• SaveMemoryTool: Saves facts, decisions, and preferences to persistent storage with automatic semantic enrichment.

• SearchMemoryTool: Searches memories using natural language with recency-aware ranking.

• DeleteMemoryTool: Removes outdated or incorrect memories by document ID.

Tool Parameters

All tools accept the following optional connection parameters that override the server's environment variable configuration on a per-call basis. When omitted, the server falls back to its configured environment variables or cluster config as usual.

This allows agents to dynamically target different clusters per tool call without reconfiguring the server (single mode only). See Dynamic Connection Parameters in the User Guide for details and examples.

In addition to the common connection parameters above, each tool accepts its own specific parameters:

Note: The opensearch_url parameter listed under individual tools below is part of the common connection parameters described above. All common connection parameters (opensearch_username, opensearch_password, aws_region, etc.) are available on every tool but are not repeated in each tool's parameter list for brevity.

• ListIndexTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (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 to

  • index (required): The name of the index to retrieve mappings for

• SearchIndexTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (required): The name of the index to search in

  • query_dsl (required): The search query in OpenSearch Query DSL format

  • format (optional): The format of SearchIndexTool response. options are csv and json

  • size (optional): The size of SearchIndexTool response. Default is 10, maximum is 100 (configurable). To change the maximum limit, set max_size_limit via CLI arguments or config file. See Tool Customization for details.

• GetShardsTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (required): The name of the index to get shard information for

• ClusterHealthTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (optional): Limit health reporting to a specific index

• CountTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (optional): The name of the index to count documents in

  • body (optional): Query in JSON format to filter documents

• ExplainTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (required): The name of the index to retrieve the document from

  • id (required): The document ID to explain

  • body (required): Query in JSON format to explain against the document

• MsearchTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (optional): Default index to search in

  • body (required): Multi-search request body in NDJSON format

• GetClusterStateTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • metric (optional): Limit the information returned to the specified metrics. Options include: _all, blocks, metadata, nodes, routing_table, routing_nodes, master_node, version

  • index (optional): Limit the information returned to the specified indices

• GetSegmentsTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (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 to

  • metrics (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 to

  • node_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 to

  • index (required): The name of the index to get detailed information for. Wildcards are supported.

• GetIndexStatsTool

  • opensearch_url (optional): The OpenSearch cluster URL to connect to

  • index (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 to

  • limit (optional): The maximum number of tasks to return. Default is 10.

• CreateAgenticMemorySessionTool

  • memory_container_id (auto-populated): The ID of the memory container where the session will be created. Automatically set when configured via agentic_memory config or OPENSEARCH_MEMORY_CONTAINER_ID env var. (Path Parameter)

  • session_id (optional): A custom session ID. If not provided, a random ID is generated. (Body Parameter)

  • summary (optional): A session summary or description. (Body Parameter)

  • metadata (optional): Additional metadata for the session provided as key-value pairs. (Body Parameter)

  • namespace (optional): Namespace information for organizing the session. (Body Parameter)

• AddAgenticMemoriesTool

  • memory_container_id (auto-populated): The ID of the memory container to add the memory to. Automatically set when configured. (Path Parameter)

  • messages (conditional): A list of messages. Required when payload_type is conversational. (Body Parameter)

  • structured_data (conditional): Structured data content. Required when payload_type is data. (Body Parameter)

  • binary_data (optional): Binary data content encoded as a Base64 string for binary payloads. (Body Parameter)

  • payload_type (required): The type of payload. Valid values are conversational or data. See Payload types. (Body Parameter)

  • namespace (optional): The namespace context for organizing memories (for example, user_id, session_id, or agent_id). If session_id is not specified in the namespace field and disable_session: false (default is true), a new session with a new session ID is created. (Body Parameter)

  • metadata (optional): Additional metadata for the memory (for example, status, branch, or custom fields). (Body Parameter)

  • tags (optional): Tags for categorizing memories. (Body Parameter)

  • infer (optional): Whether to use an LLM to extract key information (default: false). When true, the LLM extracts key information from the original text and stores it as a memory. See Inference mode. (Body Parameter)

• GetAgenticMemoryTool

  • memory_container_id (auto-populated): The ID of the memory container from which to retrieve the memory. Automatically set when configured. (Path Parameter)

  • type (required): The memory type. Valid values are sessions, working, long-term, and history. (Path Parameter)

  • id (required): The ID of the memory to retrieve. (Path Parameter)

• SearchAgenticMemoryTool

  • memory_container_id (auto-populated): The ID of the memory container. Automatically set when configured. (Path Parameter)

  • type (required): The memory type. Valid values are sessions, working, long-term, and history. (Path Parameter)

  • query (required): The search query using OpenSearch query DSL. (Body Parameter)

  • sort (optional): Sort specification for the search results. (Body Parameter)

• UpdateAgenticMemoryTool

  • memory_container_id (auto-populated): The ID of the memory container. Automatically set when configured. (Path Parameter)

  • type (required): The memory type (sessions, working, or long-term).(Path Parameter)

  • id (required): The ID of the memory to update.(Path Parameter)

  • Session memory request fields:

    • summary (optional): The summary of the session. (Body Parameter)

    • metadata (optional): Additional metadata for the memory (for example, status, branch, or custom fields). (Body Parameter)

    • agents (optional): Additional information about the agents. (Body Parameter)

    • additional_info (optional): Additional metadata to associate with the session. (Body Parameter)

  • Working memory request fields

    • messages (optional): Updated conversation messages (for conversation type). (Body Parameter)

    • structured_data (optional): Updated structured data content (for data memory payloads). (Body Parameter)

    • binary_data (optional): Updated binary data content (for data memory payloads). (Body Parameter)

    • tags (optional): Updated tags for categorization. (Body Parameter)

    • metadata (optional): Additional metadata for the memory (for example, status, branch, or custom fields). (Body Parameter)

  • Long-term memory request fields

    • memory (optional): The updated memory content. (Body Parameter)

    • tags (optional): Updated tags for categorization. (Body Parameter)

• DeleteAgenticMemoryByIDTool

  • memory_container_id (auto-populated): The ID of the memory container from which to delete the memory. Automatically set when configured. (Path Parameter)

  • type (required): The type of memory to delete. Valid values are sessions, working, long-term, and history. (Path Parameter)

  • id (required): The ID of the specific memory to delete. (Path Parameter)

• DeleteAgenticMemoryByQueryTool

  • memory_container_id (auto-populated): The ID of the memory container from which to delete the memory. Automatically set when configured. (Path Parameter)

  • type (required): The type of memory to delete. Valid values are sessions, working, long-term, and history. (Path Parameter)

  • query (required): The OpenSearch DSL query to match memories for deletion. (Body Parameter)

• DataDistributionTool

  • index (required): Target OpenSearch index name.

  • selectionTimeRangeStart (required): Start time for analysis target period.

  • selectionTimeRangeEnd (required): End time for analysis target period.

  • timeField (required): Date/time field for filtering.

  • baselineTimeRangeStart (optional): Start time for baseline period.

  • baselineTimeRangeEnd (optional): End time for baseline period.

  • size (optional): Maximum number of documents to analyze. Default is 1000.

• LogPatternAnalysisTool

  • index (required): Target OpenSearch index name containing log data.

  • logFieldName (required): Field containing raw log messages to analyze.

  • selectionTimeRangeStart (required): Start time for analysis target period.

  • selectionTimeRangeEnd (required): End time for analysis target period.

  • timeField (required): Date/time field for time-based filtering.

  • traceFieldName (optional): Field for trace/correlation ID.

  • baseTimeRangeStart (optional): Start time for baseline comparison period.

  • baseTimeRangeEnd (optional): End time for baseline comparison period.

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User Guide

For detailed usage instructions, configuration options, and examples, please see the User Guide.

Agent Memory

The OpenSearch MCP server includes two distinct memory systems. Both use OpenSearch as the storage backend but differ in who controls the memory lifecycle and what infrastructure they require.

Choosing the right approach

Use Memory Tools when you want a lightweight, agent-driven memory layer that works out of the box with any MCP-compatible IDE. The agent controls what gets remembered. See the Agent Memory Guide for setup.

Use Agentic Memory Tools when you want OpenSearch to own the full memory lifecycle — including LLM-based extraction of facts from raw conversations, structured memory types, and server-managed namespacing. See the Agent Memory Guide for setup.

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.