AgentIndex icon
AgentIndex
agents-remember logo
agents-remember
★ 31
vs
enquire-mcp logo
enquire-mcp
★ 34

agents-remember vs enquire-mcp

agents-remember: Agents Remember provides coding agents with durable, git-verified repository memory, ensuring project-specific rules are surfaced precisely when edits are made. It turns local invariants, naming rules, and other project facts into versioned Markdown files alongside the code, improving agents' ability to make safe and compliant changes.; enquire-mcp: enquire-mcp transforms your Obsidian vault into persistent, queryable long-term memory for various AI agents, eliminating the need to re-explain context in every session. It provides best-in-class hybrid retrieval, including semantic search, reranking, and HNSW, all running locally with zero cloud calls during serving.

01

TL;DR

agents-remember logo
agents-rememberMemory & Context · ★ 31

Ensuring coding agents adhere to project-specific rules and invariants when making changes deep within a codebase.

Read agents-remember full review →
enquire-mcp logo
enquire-mcpMemory & Context · ★ 34

Long-term memory for AI agents: Provides durable, semantic recall for agents across sessions, models, and providers, grounded in your Obsidian notes.

Read enquire-mcp full review →
02

Side-by-Side Comparison

Field
agents-remember logoagents-remember
enquire-mcp logoenquire-mcp
Category
Memory & Context
Memory & Context
Stars
★ 31
★ 34
License
MIT
MIT
Install Command
uvx agents-remember-mcp@latest --config /absolute/path/to/agents-remember-settings.json
npm install -g @oomkapwn/enquire-mcp
Updated
1d ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Agents, Coding Assistant, Git Integration
AI Agents, Long-term Memory, RAG
03

Features

agents-remember logoagents-remember
01Path-addressed memory: Notes live at deterministic mirror paths, providing agents with relevant context without search or guesswork.
02Git-proven freshness: Memory (notes, overviews, catalogs) is drift-checked against source commits and scopes to ensure accuracy.
03Memory that lands with code: External memory repos use ledgers and dual worktrees to synchronize code and memory updates after approval.
04Repo-owned agent behavior: Each memory repo carries system files for path rules, tools, coding guidelines, and documentation sources.
enquire-mcp logoenquire-mcp
01Vendor-neutral memory: Your memory lives in .md files, ensuring portability across different AI agents and providers.
02Best-in-class hybrid retrieval: Features BM25, multilingual embeddings, BGE cross-encoder reranker, HNSW, and int8 quantization for superior search quality and performance.
03Zero cloud calls during serve: All models are cached locally, and vault content never leaves your machine, ensuring privacy and air-gap safety.
04Freshness-aware recall: Search hits report note age and a `stale` flag, with optional recency-weighted ranking to prioritize fresh knowledge.
05PDFs with OCR & GraphRAG-light: Integrates PDFs (including OCR for scanned docs) into hybrid search and offers GraphRAG-light for wikilink community detection.
04

Use Cases

agents-remember logoagents-remember
↳Ensuring coding agents adhere to project-specific rules and invariants when making changes deep within a codebase.
↳Providing agents with critical context like naming rules, migration scars, or 'looks safe but is not' facts at the point of edit.
↳Maintaining synchronized documentation and code, with memory updates landing only after approved code changes.
↳Bootstrapping new projects or onboarding agents with predefined path rules, tools, and coding guidelines.
enquire-mcp logoenquire-mcp
↳Long-term memory for AI agents: Provides durable, semantic recall for agents across sessions, models, and providers, grounded in your Obsidian notes.
↳Personal knowledge base / second brain: Offers hybrid retrieval across 50+ languages, wikilink graph-boost, and GraphRAG-light to surface relevant notes and discover connections.
↳Agentic RAG / context engineering: Exposes per-signal scores, HyDE pre-rewrites, and sub-question decomposition for advanced retrieval, plus a built-in evaluation harness.
FAQ

FAQ

What is the difference between agents-remember and enquire-mcp?
Both agents-remember and enquire-mcp are in the Memory & Context category. agents-remember has 31 stars, while enquire-mcp has 34 stars.
Which is better, agents-remember or enquire-mcp?
The best choice depends on your use case. Choose agents-remember if Ensuring coding agents adhere to project-specific rules and invariants when making changes deep within a codebase., and enquire-mcp if Long-term memory for AI agents: Provides durable, semantic recall for agents across sessions, models, and providers, grounded in your Obsidian notes..
Is agents-remember free or open source?
Yes, agents-remember is open source on GitHub (MIT).
Is enquire-mcp free or open source?
Yes, enquire-mcp is open source on GitHub (MIT).
Cloud Infrastructure
Ad

Deploy on DigitalOcean

Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.

Claim $200 Free Credit
→

Related

Alternatives to agents-remember →Alternatives to enquire-mcp →agents-remember details →enquire-mcp details →