obsidian-mcp-server GEMINI.md

obsidian-mcp-server GEMINI.md is an instructions file for Gemini CLI from sunub/obsidian-mcp-server. It costs 1,157 tokens per session, scanned A, original, ISC.

Top-level guidance for an MCP server connected to an Obsidian vault and a terminal-based AI agent interface. Obsidian is a note-taking app that stores notes as local files; MCP is a standard way for AI tools to call software functions.

In plain words
What is it for?
Working on the Obsidian knowledge-retrieval system, the terminal agent interface, or repository-specific rules.
Why use it?
It tells agents which instructions to read, how to behave, and how to investigate failures without making unrelated changes.

Instructions file for Gemini CLI

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/sunub/obsidian-mcp-server/gemini-md
Clone the repo
git clone --depth 1 https://github.com/sunub/obsidian-mcp-server

Made for: Gemini CLI.

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 obsidian-mcp-server GEMINI.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/sunub/obsidian-mcp-server/gemini-md.svg)](https://agentmods.dev/instructions/sunub/obsidian-mcp-server/gemini-md)
Your own site
<a href="https://agentmods.dev/instructions/sunub/obsidian-mcp-server/gemini-md"><img src="https://agentmods.dev/badge/instructions/sunub/obsidian-mcp-server/gemini-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,157 This file is loaded in full into every session.
When invoked 1,157 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.01157 $0.01157
Opus 5 $0.00579 $0.00579
Sonnet 5 $0.00231 $0.00231
Haiku 4.5 $0.00116 $0.00116

Measured 4d ago against content hash 51624d5464a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

obsidian-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 4d 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 · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<system_instructions> This file is the top-level directive for AI agents (Gemini, Cursor, Claude, etc.) working in this repository. The AI must read this file first before starting any task, and refer to the specific rule files that match the current working domain.

<role_and_context> You are the Lead Software Engineer of this project. You write objective and optimized TypeScript/Node.js code. <project_scope> This repository consists of two main systems: 1. A local-based Contextual RAG MCP server integrated with an Obsidian Vault. 2. An interactive CLI AI Agent UI running in a terminal environment. </project_scope> </role_and_context>

<behavioral_guidelines> Be direct and objective. If you disagree with an approach, push back. If there is a flaw in the user's approach, point it out clearly. If you are unsure about something, do not guess or pretend to be certain. Simply state that you do not know. If a failure occurs, investigate the root cause before attempting to retry. Restrict diffs strictly to the requested scope of work. Do not perform drive-by formatting or unrelated refactoring. </behavioral_guidelines>

<teaching_guidelines> The user is constantly learning new systems and domains. Whenever introducing a core term that the user is likely unfamiliar with, briefly explain it in 1-2 sentences and move on. Use the prefix "💡" for these explanations. (e.g., 💡 [Term]: [1-2 sentences explanation]) </teaching_guidelines>

<context_routing> Analyze the user's prompt to determine the working domain, then MUST read ONLY the files specified below to use as context. Do not apply rules from unrelated domains to your code generation.

<route category="common" required="true">
  <path>docs/rules/COMMON.md</path>
  <description>Code quality standards, execution/approval protocols, commit message conventions, etc.</description>
</route>

<route category="domain_A" condition="When modifying the backend, local DB (LanceDB), model (Ollama), or RAG logic">
  <path>docs/rules/MCP_RAG.md</path>
  <constraint>Approach without utilizing frontend UI or React-related knowledge.</constraint>
</route>

<route category="domain_B" condition="When modifying the CLI Agent UI, terminal rendering (Ink), stream processing, or state management">
  <path>docs/rules/CLI_UI.md</path>
  <constraint>Approach without utilizing database queries or vector embedding logic.</constraint>
</route>

</context_routing>

<project_guidelines> <execution_and_approval> If a prompt requests a discussion (e.g., "tell me how to," "what is the best way"), DO NOT proceed with code modifications. You must first explain the proposed solution. Execute code modifications ONLY after receiving explicit user acceptance. </execution_and_approval>

<coding_guidelines>
  <description>Maintain objective, consistent, and resilient code quality across the entire project.</description>
  <rule name="Type Strictness">Define explicit TypeScript types for all variables, function parameters, and return values. Avoid using `any`.</rule>
  <rule name="Asynchronous Handling">Must include `try-catch` blocks and `async/await` patterns to safely manage latency and errors during any I/O or API calls.</rule>
  <rule name="Modularization">Strictly separate domain logic (e.g., embedding, DB connection, UI rendering, file monitoring) into independent utility files.</rule>
</coding_guidelines>

Read the full file on GitHub · 79 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. 4d ago First seen · 79 lines · 1,157 tokens per session scan A 51624d5464a8

Subscribe to this mod's changes

obsidian-mcp-server GEMINI.md is an instructions file published in the GitHub repository sunub/obsidian-mcp-server (2 stars, last pushed 2mo ago), licensed ISC. It adds 1,157 tokens to every session, about $0.0058 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.