AgentIndex icon
AgentIndex
enquire-mcp logo
enquire-mcp
★ 34
vs
telemem logo
telemem
★ 494

enquire-mcp vs telemem

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.; telemem: TeleMem is an advanced agent memory management layer, offering high-performance, character-aware, long-term, and multimodal memory capabilities for conversational AI. It significantly improves memory accuracy and speed, supporting complex scenarios like multi-turn dialogues and video content understanding.

01

TL;DR

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 →
telemem logo
telememMemory & Context · ★ 494

Developing multi-character virtual agent systems and NPCs.

Read telemem full review →
02

Side-by-Side Comparison

Field
enquire-mcp logoenquire-mcp
telemem logotelemem
Category
Memory & Context
Memory & Context
Stars
★ 34
★ 494
License
MIT
Apache-2.0
Install Command
npm install -g @oomkapwn/enquire-mcp
pip install "telemem[all]"
Updated
1d ago
4d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Agents, Long-term Memory, RAG
Agent Memory, Multimodal AI, Long-term Memory
03

Features

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.
telemem logotelemem
01Automatic, isolated per-character memory profiles for multi-persona agents.
02Full multimodal memory pipeline for video understanding and ReAct-style video QA.
03LLM-based semantic clustering and deduplication for improved memory consistency.
04High-performance, efficient asynchronous writing with batch flush.
05Fully local operation by default with support for various LLM providers.
04

Use Cases

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.
telemem logotelemem
↳Developing multi-character virtual agent systems and NPCs.
↳Building long-memory AI assistants for customer service, companionship, or creative co-pilots.
↳Enabling complex narrative and world-building in virtual environments.
↳Powering video content Q&A and reasoning for long video understanding.
↳Managing multimodal agent memory in scenarios with strong contextual dependencies.
05

Best For

enquire-mcp logoenquire-mcp
—
telemem logotelemem
Hidden Gem
FAQ

FAQ

What is the difference between enquire-mcp and telemem?
Both enquire-mcp and telemem are in the Memory & Context category. enquire-mcp has 34 stars, while telemem has 494 stars.
Which is better, enquire-mcp or telemem?
The best choice depends on your use case. Choose 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., and telemem if Developing multi-character virtual agent systems and NPCs..
Is enquire-mcp free or open source?
Yes, enquire-mcp is open source on GitHub (MIT).
Is telemem free or open source?
Yes, telemem is open source on GitHub (Apache-2.0).
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Related

Alternatives to enquire-mcp →Alternatives to telemem →enquire-mcp details →telemem details →