Ai Memory MCP
Persistent memory for any AI — MCP server, HTTP API, CLI. Works with Claude, ChatGPT, Grok, Gemini, Codex, Cursor, OpenClaw, and any MCP client. One Rust binary; SQLite or PostgreSQL + Apache AGE + pgvector; rust-a2a wake plane. Apache-2.0.
Is Ai Memory MCP safe? Thin or incomplete trust evidence. Review carefully before production use.
Compare Ai Memory MCP
How does it stack up against its MCP Servers neighbours?
Pick any agent to compare →In detail: Ai Memory MCP scores 51.0/100 (Grade C), ranked #983 of 1387 tracked open-source AI agent projects, on evidence coverage C (2 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 4.6/10; 100% of recent commits are signed; last pushed 2026-11-10. Every point is earned from checkable signals — never paid placement. How scoring works →
How Ai Memory MCP could raise its score
Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.
- Raise the OSSF Scorecard from 4.6 to 9.0lowest checks: CII-Best-Practices 0, Code-Review 0, Dependency-Update-Tool 0 +9.1 → 60.1 C · #380 of 779
Chain of custody
Scanners check what the code says. This traces who ships Ai Memory MCP and whether that has changed: from the source repository, through how changes are reviewed and released, to the code you run. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities.
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Source Signed
github.com/alphaonedev/ai-memory-mcp, Apache-2.0, last pushed 2026-11-10. 100% of the last 100 commits carry a verified signature, so changes trace to a verified account.
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Review and release Mixed
OpenSSF Scorecard rates the repository's practices 4.6/10 (scanned Nov 7, 2026). The checks that decide who can get a change released:
- Code Review0
- Branch Protection3
- Signed Releases0
- Dangerous Workflow10
- Token Permissions0
- Pinned Dependencies0
All 18 Scorecard checks
Binary-Artifacts 10Branch-Protection 3CI-Tests 10CII-Best-Practices 0Code-Review 0Contributors 3Dangerous-Workflow 10Dependency-Update-Tool 0Fuzzing 10License 10Maintained 10Packaging 10Pinned-Dependencies 0SAST 0Security-Policy 10Signed-Releases 0Token-Permissions 0Vulnerabilities 0 -
Published packages None
Distributed as the container image ghcr.io/alphaonedev/ai-memory:0.5.1; HVTracker doesn't check that registry's source link yet.
Changes to this chain
- 2026-08-30 OSSF Scorecard: 4.5/10
Evidence behind this score
Coverage C: 2 of 5 independent evidence types found.
- GitHub repository data
- Package downloads (missing)
- Supply-chain checks
- Public actions (missing)
- Community mentions (missing)
Verify this score yourself
Every build re-issues Ai Memory MCP’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.
What this score doesn’t check
It covers who ships the code, not what the code does. It doesn’t read tool descriptions or prompts for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you connect it, such as Cisco MCP Scanner or Snyk Agent Scan.
How Ai Memory MCP compares in MCP Servers
- #551 Glif 51.2 +0.2
- #552 Microsoft MCP Server for Enterprise 51.2 +0.2
- #553 Ai Memory MCP 51.0 this agent
- #554 Serpapi MCP 51.0 ±0
- #555 Greptimedb MCP Server 50.9 −0.1
Bars show each HVTrust score; the tick marks Ai Memory MCP’s 51.0.
Where the 51.0 comes from
HVTrust dimensions vs the MCP Servers average
51.0 / 100 · 100.0% confidenceAi Memory MCP MCP Servers average (779 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade C reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage C is separate — it grades how many independent signal types back the score (2 of 5), so a high score on thin evidence stays visible. Full methodology →
Rank Trend
Activity & Reach
Analysis
Activity Inputs
51.7 / 100Common questions about Ai Memory MCP
Does Ai Memory MCP publish package provenance?
Does Ai Memory MCP have an OpenSSF Scorecard?
Is Ai Memory MCP actively maintained?
What license does Ai Memory MCP use?
Are Ai Memory MCP's commits signed?
Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.
AI agent surface
MCP, providers, tool surface
These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Detected changes to Ai Memory MCP's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.
Maintain Ai Memory MCP?
For maintainers
HVTrust scores Ai Memory MCP from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.
Reputation Timeline
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/ai-memory-mcp)
<a href="https://hvtracker.net/agents/ai-memory-mcp"><img src="https://hvtracker.net/badge/ai-memory-mcp.svg" alt="HVTrust"></a>
Other agents in MCP Servers
GitHub REST API (repo, commits, stars, forks, license) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON