# Prismer-AI/PrismerCloud

Prismer Cloud

Repository: https://github.com/Prismer-AI/PrismerCloud
Canonical: https://ross.abutalabs.com/products/prismercloud
Homepage: https://prismer.cloud
Language: TypeScript
License: MIT
License Family: permissive
Topics: agent-communication, agent-memory, ai-agents, claude, cursor, docker, knowledge-base, llm-tools, mcp, mcp-server, nextjs, rag, self-hosted, typescript, windsurf
Last push: 2026-08-06T18:33:46+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 96, release rhythm 80, longevity 11
- inputs: {"age_days": 165, "days_push": 27, "days_rel": 134, "gap_med": 6.0, "n_releases_24m": 5}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1409, forks 12 (observed 2026-08-28T04:04:38.682637+00:00)

## What it is
Prismer Cloud is a hosted/self-hostable knowledge infrastructure platform for AI agents, providing context fetching and compression, document parsing with OCR, agent-to-agent messaging, shared memory, and an evolution engine that transfers learned strategies across agents. It ships SDKs in TypeScript, Python, Go, and Rust, plus an MCP server and plugins for Claude Code, Cursor, and Windsurf.

## Use cases
- give my AI agent persistent memory across sessions
- let agents communicate and share knowledge with each other
- parse PDFs and scanned documents into LLM-friendly context
- add MCP tools to Claude Code or Cursor
- build a shared knowledge base for a fleet of agents
- manage agent identity with DID and verifiable credentials
- self-host a messaging platform for AI agents

## When to choose
- you need cross-agent memory, messaging, and learned-strategy sharing out of the box
- you want MCP integration with coding assistants like Claude Code, Cursor, or Windsurf
- you need document parsing and web context fetching optimized for LLM context windows

## When to avoid
- you only need a simple local vector store or RAG pipeline without agent communication
- you require fully offline operation with no external service dependency
- you want a mature, widely-adopted platform rather than a young project

## Facets
- artifact type: service
- maturity: active
- function: rag, mcp, agent-framework, message-queue, caching, ocr, search-engine, web-scraping, auth, websocket, sdk
- domain: large-language-models, messaging-platforms, apis, self-hosted, developer-tools
- platform: self-hosted, cloud
- tags: agent-memory, agent-communication, agent-identity, did, skill-marketplace, claude-code, cursor, windsurf, context-api, evolution-engine, knowledge-base, mcp-server, ai-agents, retrieval-augmented-generation, docker, nodejs, typescript, web-server

## Member repositories
- Prismer-AI/PrismerCloud (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:38.682637+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:38:30.976478+00:00, confidence not recorded.
  - readme: https://github.com/Prismer-AI/PrismerCloud (fetched 2026-08-28T04:04:38.682637+00:00, sha 28b9b9465a60)
  - homepage: https://prismer.cloud (fetched 2026-08-29T11:52:16.266357+00:00, sha 2224d8aeb310)
  - site_page: https://prismer.cloud/docs (fetched 2026-08-29T11:52:16.275210+00:00, sha 25c1665b755d)
  - site_page: https://prismer.cloud/about (fetched 2026-08-29T11:52:16.279142+00:00, sha 1122c79d726d)
  - site_page: https://prismer.cloud/pricing (fetched 2026-08-29T11:52:16.277347+00:00, sha c0c4e2bd2e5e)
- Data as of 2026-08-30T08:39:29.467469+00:00.