OpenSearch MCP Server
Enables retrieval of error stack traces by transaction ID from OpenSearch logs, supporting configurable connection settings and Docker deployment.
README
OpenSearch MCP Server
A Model Context Protocol (MCP) server built with FastMCP for retrieving error stack traces by transaction ID (TID) from OpenSearch logs.
Features
- Error stack trace retrieval: Get complete error stack traces by transaction ID (TID)
- Docker-based setup: Easy local development with Docker Compose
- Environment variable configuration: Flexible connection settings via environment variables
Prerequisites
- Python 3.10 or higher
- Docker and Docker Compose (for running the MCP server in a container)
- An accessible OpenSearch instance (you provide your own)
- pip or uv for package management
Installation
- Clone the repository:
git clone <repository-url>
cd opensearch-mcp
- Install dependencies:
pip install -r requirements.txt
Or using uv:
uv pip install -r requirements.txt
- Set up environment variables (optional):
cp .env.example .env
# Edit .env with your OpenSearch connection settings
Quick Start
Prerequisites: You need your own OpenSearch instance running and accessible. Configure the connection details in the .env file.
Option 1: Using Docker Compose (Recommended)
- Copy the environment file and configure your OpenSearch connection:
cp .env.example .env
# Edit .env and set OPENSEARCH_HOST and OPENSEARCH_PORT to your OpenSearch instance
- Start the MCP server:
docker-compose up
This will start:
- MCP server on port 48081 (HTTP endpoint:
http://localhost:48081/mcp)
The MCP server will connect to your OpenSearch instance using the configuration from .env.
To run in detached mode:
docker-compose up -d
Option 2: Run MCP Server directly with Python
- Set up environment variables:
cp .env.example .env
# Edit .env and configure OPENSEARCH_HOST and OPENSEARCH_PORT to your OpenSearch instance
- Run the MCP server:
python server.py
The server will start on http://localhost:48081/mcp.
Option 3: Run MCP Server with Docker (standalone)
- Build the Docker image:
docker build -t opensearch-mcp .
- Run the container with your OpenSearch connection details:
docker run --rm -p 48081:48081 \
-e OPENSEARCH_HOST=your-opensearch-host \
-e OPENSEARCH_PORT=9200 \
opensearch-mcp
Or use an env file:
docker run --rm -p 48081:48081 --env-file .env opensearch-mcp
The MCP server will be available at http://localhost:48081/mcp.
Note:
- Replace
your-opensearch-hostwith your actual OpenSearch hostname or IP - Use
host.docker.internal(macOS/Windows) or your host IP (Linux) if OpenSearch is running on the host machine - For remote instances, use the actual hostname or IP address
Configuration
The MCP server reads connection settings from environment variables:
| Variable | Default | Description |
|---|---|---|
OPENSEARCH_HOST |
localhost |
OpenSearch host |
OPENSEARCH_PORT |
9200 |
OpenSearch port |
OPENSEARCH_USE_SSL |
false |
Enable SSL/TLS |
OPENSEARCH_VERIFY_CERTS |
false |
Verify SSL certificates |
OPENSEARCH_USERNAME |
- | Username for authentication (optional) |
OPENSEARCH_PASSWORD |
- | Password for authentication (optional) |
When using Docker Compose, these variables are automatically available from the container environment.
MCP Tools
stack_trace_tid
Retrieve full error stack trace by transaction ID (TID).
Parameters:
tid(string, required): Transaction ID to search forindex_pattern(string, optional): Index pattern to search (default:servicelogs-*)repo_name(string, optional): Filter by repository/application name (maps toapplication_namefield)
Example:
{
"tid": "e1020584c0a74074a930c4e90e953912.139.17702793574644017",
"repo_name": "xxx"
}
Returns: Formatted text with one log entry per line. Each line follows the format:
timestamp - level - message - application_name - project
If a separate stack_trace field exists in the log document, the format is:
timestamp - level - message - stack_trace - application_name - project
Note: Log entries are sorted chronologically by @timestamp in ascending order. Newlines in messages and stack traces are normalized to | (pipe characters) for single-line format.
Example Output:
2026-02-05T08:15:57.566Z - INFO - channel GOPAY got phone A0:1ec614bbcb328b7c66436a318d7b77e0 from token - xxx - xxx
2026-02-05T08:15:57.570Z - INFO - register user for A0:44b351780fec875b97ad01d9bb946f3e , system : SYSTEM_TYPE_ATOME, channel: GOPAY - user-service-provider - pintar-user
2026-02-05T08:15:58.263Z - ERROR - POST http://:8080/user/info -d [{"module":"RESIDENTIAL_INFO","module":"RESIDENTIAL_INFO",...}] ***RESPONSE*** 400 {"timestamp":1770279358262,"status":400,"error":"Bad Request","path":"/user/info"} - xxx - xxx
2026-02-05T08:15:58.264Z - ERROR - [Gopay Linking] Failed to save user info for userId : [400 ] during [POST] to [http://:8080/user/info] [PintarUserInfoFeignClient#saveUserInfo(List)]: [{"timestamp":1770279358262,"status":400,"error":"Bad Request","path":"/user/info"}] - feign.FeignException$BadRequest: [400 ] during [POST] to [http://:8080/user/info] [PintarUserInfoFeignClient#saveUserInfo(List)]: [{"timestamp":1770279358262,"status":400,"error":"Bad Request","path":"/user/info"}] | at feign.FeignException.clientErrorStatus(FeignException.java:243) | at feign.FeignException.errorStatus(FeignException.java:223) | at feign.FeignException.errorStatus(FeignException.java:213) | ... - xxx - xxx
2026-02-05T08:15:58.267Z - INFO - [GopayServiceImpl] linking account failed for userId: , error: INVALID_KYC - xxx - xxx
Note: Log entries are sorted by timestamp in ascending order. Stack traces (when present) are included as part of the message field, with stack frames separated by | (pipe characters).
Usage with MCP Clients
The MCP server uses streamableHttp transport on port 48081. This enables HTTP-based communication instead of stdio, making it easier to deploy and scale.
Starting the Server
Important: Ensure your OpenSearch instance is running and accessible before starting the MCP server.
Option 1: Using Docker Compose (Recommended)
- Configure your OpenSearch connection in
.env:
cp .env.example .env
# Edit .env with your OpenSearch host and port
- Start the MCP server:
docker-compose up
The MCP server will be available at http://localhost:48081/mcp.
Option 2: Running Locally
- Set up environment variables:
cp .env.example .env
# Edit .env with your OpenSearch host and port
- Run the MCP server:
python server.py
The server will start on http://localhost:48081/mcp.
Option 3: Using Docker Run
Build the image:
docker build -t opensearch-mcp .
Run the container with your OpenSearch connection:
docker run --rm -p 48081:48081 \
-e OPENSEARCH_HOST=your-opensearch-host \
-e OPENSEARCH_PORT=9200 \
opensearch-mcp
Or use an env file:
docker run --rm -p 48081:48081 --env-file .env opensearch-mcp
Configuring MCP Clients
Cursor IDE
Add to your Cursor MCP settings (mcp.json):
{
"mcpServers": {
"opensearch": {
"url": "http://localhost:48081/mcp"
}
}
}
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"opensearch": {
"url": "http://localhost:48081/mcp"
}
}
}
Remote Access
If the MCP server is running on a remote machine, use the remote URL:
{
"mcpServers": {
"opensearch": {
"url": "http://your-server-ip:48081/mcp"
}
}
}
Configuration
The MCP server port and host can be configured via environment variables:
MCP_PORT: Port for the HTTP server (default: 48081)MCP_HOST: Host to bind to (default: 0.0.0.0)
Example:
MCP_PORT=8080 MCP_HOST=127.0.0.1 python server.py
Docker Networking Notes
- Local development: Use
http://localhost:48081/mcp - VPN Access: The docker-compose.yml uses
network_mode: hostto allow the container to access VPN resources through your host's network - Docker Compose: When using host network mode, the container shares your host's network stack, including VPN connections
- Remote access: Ensure port 48081 is accessible from your MCP client
Note: With network_mode: host, the container uses your host's network directly, so:
- VPN resources are accessible from the container
- No port mapping is needed (ports are directly accessible on the host)
- The container can access resources that require VPN connection
Development
Project Structure
opensearch-mcp/
├── src/
│ └── opensearch_mcp/
│ ├── __init__.py
│ ├── server.py # FastMCP server with tool definitions
│ └── opensearch_client.py # OpenSearch client wrapper
├── docker-compose.yml # Docker Compose setup (OpenSearch + MCP server)
├── Dockerfile # MCP server Docker image
├── .dockerignore # Docker ignore file
├── .env.example # Example environment variables
├── mcp.json.example # Example MCP client configuration
├── requirements.txt # Python dependencies
├── pyproject.toml # Python project configuration
└── README.md # This file
Running Tests
# Ensure your OpenSearch instance is running and accessible
# Start MCP server with Docker Compose
docker-compose up
# Or run MCP server locally
python server.py
Docker Compose Services
The docker-compose.yml includes only the MCP server service:
- opensearch-mcp: MCP server (uses
.envfile for configuration)
The MCP server service:
- Builds from the local Dockerfile
- Loads environment variables from
.envfile - Connects to your OpenSearch instance using the configuration from
.env - Exposes HTTP endpoint on port 48081 at
/mcppath - Uses streamableHttp transport for MCP communication
Note: You need to provide your own OpenSearch instance. Configure the connection details in the .env file.
Log Data Format
The MCP server expects log documents with the following structure:
{
"@timestamp": "2024-01-01T10:00:00Z",
"level": "ERROR",
"msg": "Error occurred...",
"application_name": "xxx",
"project": "xxx",
"stack_trace": "feign.FeignException$BadRequest: [...] | at ...",
"TID": "e1020584c0a74074a930c4e90e953912.139.17702793574644017"
}
Key fields:
@timestamp: Log timestamp (ISO 8601 format)level: Log level (INFO, WARN, ERROR, etc.)msg: Log message contentapplication_name: Application/service name (used for filtering viarepo_nameparameter)project: Project/repository namestack_trace: Stack trace content (optional, formatted as pipe-separated lines)TID: Transaction ID field (searched using phrase matching across all fields)
Troubleshooting
Connection Errors
If you see connection errors:
- Ensure your OpenSearch instance is running and accessible
- Check OpenSearch health:
curl http://your-opensearch-host:9200/_cluster/health - Verify environment variables in
.envare set correctly (OPENSEARCH_HOST and OPENSEARCH_PORT) - If running in Docker, ensure the container can reach your OpenSearch instance (network configuration)
No Results Found
- Check that your index pattern matches existing indices (default:
servicelogs-*) - Verify that the TID exists in your log documents (searched using phrase matching across all fields)
- If using
repo_namefilter, verify thatapplication_namefield exists and matches the filter value - Ensure the TID format matches what's stored in your logs
SSL/TLS Issues
If using SSL:
- Set
OPENSEARCH_USE_SSL=true - Configure
OPENSEARCH_VERIFY_CERTSappropriately - Provide CA certificates if needed
License
MIT
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.