CueMap
Memory layer written in Rust that stores and recalls context for AI applications, with local semantic reranking.
23 linking domains
Emerging
- Price
- Price not read
- Activity
- Actively maintainedrelease 4 weeks ago
- Company
- Domain since 2025domain registered
- Domain since2025domain registered
- MCP serverio.github.cuemap-dev/cuemap-mcppublished by cuemap-dev on GitHub
- Statenot asked yet
Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.
Figure and bar: visits/mo, estimate · year: online since
- #1
Supermemory MCP
Stores and retrieves learned context for agents using a vector graph database, injecting relevant memories into model prompts in real time.
4.6kActiveFrom $19/mo - #2
Nerra
Builds a shared memory layer from your company tools and serves it to AI agents over MCP.
31Active—2024 - #3
Phoenix Grove Systems™
Provides access to open-source language models with privacy-first architecture and persistent memory across conversations.
22Active— - #4
memgram
Stores and retrieves contextual memory for AI agents across conversations with inspection and governance.
18not readFrom $29/mo - #5
Paxs
Provides a continuously learning memory layer for AI agents that evolves in place without forgetting.
14Active— - #6
AgentPrizm
Provides persistent, auditable memory layer for AI agents via API and MCP protocol.
2ActiveFrom $19/mo
What is CueMap?
Memory layer written in Rust that stores and recalls context for AI applications, with local semantic reranking. It is listed in the Atlas under LLM operations.
Do people use CueMap?
Emerging.
Is CueMap still maintained?
Actively maintained: release 4 weeks ago.
What are alternatives to CueMap?
In LLM operations, by use: Supermemory MCP, Nerra, Phoenix Grove Systems™, memgram, Paxs, AgentPrizm.
Not quite it? Describe the job
betaFive tools from the Atlas that fit it, each judged against what you wrote.
How we read a tool
No votes, no reviews, no vendor claims. Every week a crawler reads each tool's own site and a few public registries, and the words on the card are bands over what it read.
- Use: visits to the site (estimated), installs from npm and PyPI, presence in Chrome's usage report.
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- The line and the use cases are written by us from the homepage, one tool at a time, and refused when they repeat the vendor's marketing.
How AI assistants read each site — the reading vendors ask us about — is on each tool's own visibility page.