Borrowing it
Nothing to install: this file belongs to myx0423/tech-memory-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/myx0423/tech-memory-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/myx0423/tech-memory-mcpWrote 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.
[](https://agentmods.dev/instructions/myx0423/tech-memory-mcp/agents-md)<a href="https://agentmods.dev/instructions/myx0423/tech-memory-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/myx0423/tech-memory-mcp/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.
<a href="https://agentmods.dev/instructions/myx0423/tech-memory-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/myx0423/tech-memory-mcp/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02046 | $0.02046 |
| Opus 5.5 | $0.00818 | $0.00818 |
| Sonnet 5.5 | $0.00409 | $0.00409 |
| Haiku 4.5 | $0.00205 | $0.00205 |
Grade A, and why
tech-memory-mcp 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to AI coding agents when working with this codebase.
Project Overview
tech-memory-mcp is a Model Context Protocol (MCP) Server that provides long-term technical knowledge memory for AI agents. It extracts, stores, and retrieves technical knowledge from conversations using vector embeddings and SQLite.
Core purpose: Enable AI assistants to remember "what was learned" across conversations, not just "what was said".
Tech Stack
- Runtime: Node.js >= 18.0.0 (uses
better-sqlite3) - Language: TypeScript (strict mode, ES2022 target, NodeNext modules)
- Database: SQLite with FTS5 full-text search
- Embeddings: Transformers.js with
Xenova/jina-embeddings-v2-base-zh(768-dim vectors) - MCP SDK:
@modelcontextprotocol/sdkfor MCP protocol implementation - Build: TypeScript compiler (
tsc), no bundler
Architecture
src/
├── index.ts # MCP server entry point, registers all tools
├── db.ts # Database initialization, migrations, CRUD operations
├── embeddings.ts # Vector embedding pipeline (Transformers.js)
├── types.ts # Core type definitions
└── tools/ # MCP tool implementations
├── search.ts # tech_search (hybrid vector + FTS search)
├── store.ts # tech_store (store with semantic dedup)
├── auto_extract.ts # tech_auto_extract (two-phase extraction)
├── extract.ts # tech_extract_template (extraction prompt)
├── get.ts # tech_get (retrieve single entry + graph neighbors)
├── link.ts # tech_link (create knowledge relationships)
├── confirm.ts # tech_confirm (adjust confidence)
├── decay.ts # tech_decay (age-based confidence decay)
├── outdated.ts # tech_outdated (query expired entries)
└── stats.ts # tech_stats (database statistics)
Key Patterns
Adding a New MCP Tool
- Create
src/tools/<tool_name>.ts - Export a
register<ToolName>Tool(server: McpServer, db: DatabaseSync)function - Use
server.registerTool()with:description: Chinese description explaining what the tool doesinputSchema: Zod schema with.strict()to reject unknown fields- Handler: async function returning
{ content: [{ type: "text", text: string }] }
- Register the tool in
src/index.tsby calling the register function - All logging goes to
process.stderr(stdout is reserved for MCP JSON-RPC)
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.
- 2mo ago First seen · 220 lines · 2,046 tokens per session scan A 8ea43459a2c7
tech-memory-mcp AGENTS.md is an instructions file published in the GitHub repository myx0423/tech-memory-mcp (0 stars, last pushed 4mo ago), licensed MIT. It adds 2,046 tokens to every session, about $0.0082 per session on Opus 5.5. 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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