opensearch-mcp-server-py: Instructions file for Codex

AGENTS.md

opensearch-mcp-server-py AGENTS.md is an instructions file for Codex, OpenCode from opensearch-project/opensearch-mcp-server-py. It costs 376 tokens per session, scanned A, original, Apache-2.0.

Repository-specific instructions for an OpenSearch MCP server, describing where tools and parameter models live and how tool errors, helpers, and visibility categories must work.

In plain words
What is it for?
Use them when adding or changing OpenSearch tools, parameters, helper functions, error handling, logging, or tool categories.
Why use it?
They help new tools follow the server's existing contracts so errors are reported correctly and tools are available to the intended users.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is opensearch-project/opensearch-mcp-server-py's own configuration. It tells Codex and OpenCode how to work on opensearch-mcp-server-py itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything opensearch-mcp-server-py configures →

Reuse

Borrowing it

Nothing to install: this file belongs to opensearch-project/opensearch-mcp-server-py. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/opensearch-project/opensearch-mcp-server-py/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/opensearch-project/opensearch-mcp-server-py

Made for: Codex, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for opensearch-mcp-server-py AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/opensearch-project/opensearch-mcp-server-py/agents-md/github.svg)](https://agentmods.dev/instructions/opensearch-project/opensearch-mcp-server-py/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/opensearch-project/opensearch-mcp-server-py/agents-md"><img src="https://agentmods.dev/badge/instructions/opensearch-project/opensearch-mcp-server-py/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for opensearch-mcp-server-py AGENTS.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/opensearch-project/opensearch-mcp-server-py/agents-md"><img src="https://agentmods.dev/badge/instructions/opensearch-project/opensearch-mcp-server-py/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 376 This file is loaded in full into every session.
When invoked 376 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00376 $0.00376
Opus 5 $0.00188 $0.00188
Sonnet 5 $0.00075 $0.00075
Haiku 4.5 $0.00038 $0.00038

Measured 9d ago against content hash 2db8f2bd8259, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

opensearch-mcp-server-py AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 26 lines

What it actually says

Agents Guide

When adding or modifying tools, read the existing code first. The patterns are consistent — follow them.

Key files

  • src/tools/tools.py — All tool functions and TOOL_REGISTRY (the static dict of every tool)
  • src/tools/tool_params.py — All Pydantic param models (extend baseToolArgs)
  • src/opensearch/helper.py — All async helpers (OpenSearch calls, no try/except)
  • src/tools/tool_filter.py — Category system that controls tool visibility
  • src/tools/tool_logging.pylog_tool_error() — the only way to return errors from tools
  • src/mcp_server_opensearch/tool_executor.py — Executes tools, checks is_error: True for metrics

Non-obvious contracts

  • Error handling: Every tool must use log_tool_error() in its except block. It returns is_error: True which tool_executor.py relies on for monitoring. Without it, errors are silently counted as successes.
  • Helpers don't catch exceptions: Helpers in helper.py let exceptions propagate. The tool function in tools.py handles errors.
  • Tool filter categories: Tools not in any enabled category are invisible. Only core_tools is enabled by default. New tool groups need a category in tool_filter.py.
  • No special registration: All tools go in TOOL_REGISTRY statically. No tool needs custom startup logic.

Adding tools

See the Adding Custom Tools section in the Developer Guide.

For adding a large group of tools, use the Search Relevance Workbench as a blueprint — 18 tools added with zero new files or infrastructure changes.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 26 lines · 376 tokens per session scan A 2db8f2bd8259

Subscribe to this mod's changes

opensearch-mcp-server-py AGENTS.md is an instructions file published in the GitHub repository opensearch-project/opensearch-mcp-server-py (149 stars, last pushed 6d ago), licensed Apache-2.0. It adds 376 tokens to every session, about $0.0019 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other instructions, from other repositories

vibe-coding-prompt-template backend.instructions.md

Instructions for KhazP/vibe-coding-prompt-template: Read AGENTS.md, agentdocs/techstack.md, and agentdocs/codepatterns.md.

KhazP/vibe-coding-prompt-template · 139 tokens

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,153 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens