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opensearch-project

opensearch-mcp-server-py

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GenericOpenSearchApiTool

Call any OpenSearch API endpoint with full control over HTTP method, path, query parameters, body, and headers. Ideal for accessing APIs without dedicated tools.

Instructions

A flexible tool for calling any OpenSearch API endpoint. Supports all HTTP methods with custom paths, query parameters, request bodies, and headers. Use this when you need to access OpenSearch APIs that don't have dedicated tools, or when you need more control over the request. Leverages your knowledge of OpenSearch API documentation to construct appropriate requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opensearch_urlYesOpenSearch endpoint URL.
opensearch_usernameNoUsername for basic authentication.
opensearch_passwordNoPassword for basic authentication.
opensearch_no_authNoIf true, connect without authentication.
aws_regionNoAWS region for IAM/Serverless authentication.
aws_iam_arnNoIAM role ARN for role-based authentication.
aws_profileNoAWS profile name for authentication.
aws_opensearch_serverlessNoIf true, use OpenSearch Serverless service.
opensearch_ssl_verifyNoIf false, disable SSL certificate verification.
opensearch_timeoutNoConnection timeout in seconds.
pathYesThe API endpoint path (e.g., "/_search", "/_cat/indices", "/my_index/_doc/1"). Should start with "/".
methodNoHTTP method to use (GET, POST, PUT, DELETE, HEAD, PATCH)GET
query_paramsNoQuery parameters to include in the request URL as key-value pairs
bodyNoRequest body for GET/POST/PUT requests. Can be a JSON object, string, or None
headersNoAdditional HTTP headers to include in the request
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it does not disclose potential side effects, authentication requirements beyond what's in the schema, error handling, or rate limits. For a generic API tool that can perform destructive operations (e.g., DELETE), this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, comprising two well-structured sentences. It is front-loaded with the core purpose and immediately provides usage context. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the high complexity (15 parameters, no output schema, no annotations), the description is incomplete. It does not address error handling, response format, or authentication workflow beyond parameter names. The examples in the schema partially compensate, but the description itself lacks completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already fully describes each parameter (e.g., path, method, body). The description adds no additional meaning beyond 'supports all HTTP methods' and 'custom paths,' which aligns with the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a flexible tool for calling any OpenSearch API endpoint, supporting all HTTP methods and custom paths. It explicitly differentiates from siblings by noting when to use it: for APIs without dedicated tools or when more control is needed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance: 'Use this when you need to access OpenSearch APIs that don't have dedicated tools, or when you need more control over the request.' It also mentions leveraging your knowledge of OpenSearch API documentation, which helps the agent understand the expected workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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