# AgentPrizm: Persistent Agent Memory via MCP Is Here > Source: > Published: 2026-07-11 13:09:18+00:00 Every AI agent you ship today has amnesia. The context window resets at session end, prior decisions evaporate, and a coding agent that understood your architectural constraints last week doesn’t recognize them this week. [AgentPrizm](https://agentprizm.com/) launched on July 9, 2026 with a governed memory layer — available over REST and MCP — that addresses this at the infrastructure level, not the prompt level. ## The Problem Is Load-Bearing, Not Academic Developers building agents in 2026 hit a structural ceiling: LLM context windows are fast, expensive, and ephemeral. They are working memory, not storage. Agents forget instructions mid-task, lose track of user preferences, and force repeated context re-injection that inflates costs without guaranteeing consistency. The [Mem0 State of AI Agent Memory 2026](https://mem0.ai/blog/state-of-ai-agent-memory-2026) report counts 21 competing frameworks and 20 vector stores now targeting this problem — which tells you everything about how acute it has become. In 2026, the memory layer is not an optional optimization. It is load-bearing infrastructure. The gap between a prototype agent and one that survives production is almost never the model. It is [whether the agent can remember](https://beam.ai/agentic-insights/your-ai-agents-context-window-is-ram-not-storage-that-explains-most-production-failures). AgentPrizm is betting that the answer is governed, auditable memory — not just another vector store with a MCP wrapper. ## What AgentPrizm Actually Ships The platform has two parts. **AgentMemory** is the persistence layer: a REST API at `/api/v1/agent/*` plus an MCP server that works with Claude Code, Cursor, Claude Desktop, and any MCP-capable agent. Each memory carries a confidence score, a `valid_from` timestamp, and an optional `valid_to` . When a newer fact supersedes an older one, the old memory is marked stale and the supersede chain is recorded — so a decision that was correct last quarter doesn’t silently corrupt a recommendation this quarter. Every recall produces an audit receipt: a traceable log of what the agent knew and when, instead of opaque context stuffing you can’t inspect afterward. **AgentSkills** is the second half — a governed marketplace for reusable, versioned agent workflows. Teams publish versioned `SKILL.md` files, discover them by intent, and fork with full lineage. PII and secrets are blocked before any skill reaches the public marketplace. AgentSkills is included free on every plan, which makes this one of the more interesting bundling decisions in the space: persistent memory and reusable procedure in a single subscription. ## Setup and Pricing The free tier is real: 10,000 memories and 4,500 recalls per month, API and MCP access, no credit card required. For MCP clients, setup is a single config block — no local server to run, no dependencies to install. The REST API accepts any language. AgentPrizm is also available on ClawHub, OpenClaw’s public skill registry, for teams already in that ecosystem. A source-available version of the memory engine is planned for later this summer, which matters for teams with data residency requirements or compliance postures that rule out managed services. ## How It Stacks Against the Competition The [persistent agent memory MCP space is crowded](https://getunblocked.com/blog/memory-mcp-servers-compared/). Mem0 leads on community size (47K+ GitHub stars) and general-purpose use, but gates graph features at $249/month. Zep’s Graphiti engine scores better on temporal reasoning — 63.8% vs Mem0’s 49% on LongMemEval — but shipped CVE-2026-32247 (Cypher injection exploitable via prompt injection) this spring. agentmemory targets coding agents specifically at around $10/year. AgentPrizm’s angle is governance: confidence scores, audit receipts, and GDPR-native right-to-forget via a single `POST /forget` endpoint, with a signed DPA and published sub-processor list. Most competitors treat compliance as an afterthought. AgentPrizm built the compliance posture into the data model from the start. ## One Risk Worth Naming OWASP’s new MCP Top 10 flags memory poisoning — injecting malicious instructions into an agent’s long-term storage — as a real attack vector. The Zep CVE proved it is not theoretical. Any persistent memory layer expands your agent’s attack surface. AgentPrizm’s container isolation and per-recall audit receipts reduce that surface, but treat memory servers the same way you treat session stores: authenticated, access-controlled, and monitored. Audit receipts only matter if someone reads them. ## What to Watch The source-available engine is the biggest signal to track. If AgentPrizm ships self-hosted this summer, it opens up enterprise teams that cannot send data to a managed service — a large addressable market underserved by current options. Free tier is live now at [agentprizm.com](https://agentprizm.com/). The [full launch announcement](https://www.digitaljournal.com/pr/news/access-newswire/agentprizm-launches-governed-ai-agent-1203883901.html) covers the API surface in more detail.