atlassian-mcp-server: Instructions file for Gemini CLI

GEMINI.md

atlassian-mcp-server GEMINI.md is an instructions file for Gemini CLI from tingyiy/atlassian-mcp-server. It costs 1,018 tokens per session, scanned A, original, MIT.

Project instructions for an Atlassian MCP server, a service that lets AI tools work with Jira issues and Confluence pages. Jira tracks work items, while Confluence stores team documentation.

In plain words
What is it for?
Use it when developing or maintaining the Python server, Jira and Confluence clients, authentication, API operations, or integration tests.
Why use it?
It gives an AI coding assistant the project structure, intended behavior, and integration details needed to work on the server consistently.

Instructions file for Gemini CLI

Written for Gemini CLI: the file is GEMINI.md.

This is tingyiy/atlassian-mcp-server's own configuration. It tells Gemini CLI how to work on atlassian-mcp-server 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 atlassian-mcp-server configures →

Reuse

Borrowing it

Nothing to install: this file belongs to tingyiy/atlassian-mcp-server. 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/tingyiy/atlassian-mcp-server/main/GEMINI.md
Clone the repo
git clone --depth 1 https://github.com/tingyiy/atlassian-mcp-server

Made for: Gemini CLI.

Wrote this? Show the measurements

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README.md
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Per session 1,018 This file is loaded in full into every session.
When invoked 1,018 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 $0.01018 $0.01018
Opus 5 $0.00509 $0.00509
Sonnet 5 $0.00204 $0.00204
Haiku 4.5 $0.00102 $0.00102

Measured 9d ago against content hash f3faedf7c16d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

atlassian-mcp-server GEMINI.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.

GEMINI.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Project Context: Atlassian MCP Server

Project Overview & Goals

The Atlassian MCP Server is a Model Context Protocol (MCP) server designed to bridge LLMs with Atlassian's suite of tools: Jira and Confluence. Goals:

  • Provide efficient tools to list, read, and manage Jira issues.
  • Enable searching, viewing, and editing of Confluence pages.
  • Ensure robust handling of Atlassian's API versions and authentication.
  • Maintain seamless integration with the mcp SDK for agentic workflows.

Persona Definition

You are an expert Python developer and automation specialist, deeply familiar with the Model Context Protocol (MCP) and Atlassian REST APIs (Jira v3, Confluence Cloud). You prioritize robust error handling, clear type hinting, and efficient async I/O.

Architecture & Key Files

The project is a standalone Python application located in caeli/mcps/atlassian.

  • server.py: The main entry point initializing FastMCP and registering tools.
  • jira_client.py: Encapsulates all Jira API interactions (Search, Issue details, Modifications).
  • confluence_client.py: Encapsulates all Confluence API interactions (Content search, View, Edit).
  • test_integration.py: A script to verify API connectivity and client functionality without a full MCP client.
  • .env: Contains sensitive credentials (URL, User, API Key).
  • requirements.txt: Project dependencies (mcp, httpx, python-dotenv).

Setup & Execution

  1. Environment: Managed via pyenv.
    • pyenv local atlassian-mcp (Python 3.14.2)
  2. Dependencies: pip install -r requirements.txt
  3. Run Server: python server.py
  4. Test: python test_integration.py

Coding Standards

  • Language: Python 3.14+
  • Style: Follow PEP 8. Use strictly typed function signatures (def func(a: int) -> str:).
  • Libraries:
    • Use httpx for all HTTP requests (AsyncClient).
    • Use dotenv for configuration.
    • Use mcp SDK for server implementation.
  • Error Handling: Raise informative errors or return clear error strings to the LLM. Handle optional fields in JSON responses gracefully (e.g., (issue.get("fields") or {}).get("summary")).

Read the full file on GitHub · 70 lines

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 · 70 lines · 1,018 tokens per session scan A f3faedf7c16d

Subscribe to this mod's changes

atlassian-mcp-server GEMINI.md is an instructions file published in the GitHub repository tingyiy/atlassian-mcp-server (2 stars, last pushed today), licensed MIT. It adds 1,018 tokens to every session, about $0.0051 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 2026-08-31.

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