原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

World Model MCP

作者:SaravananJaichandar版本 0.15.5i★ –i在你的电脑上运行
注册名称io.github.SaravananJaichandar/world-model-mcp

安装

概览

作者提供的说明(英文原文)

Temporal knowledge graph for codebases with constraint enforcement at the edit boundary.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆
  • 你需要填写:ANTHROPIC_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: WORLD_MODEL_DB_PATH, ANTHROPIC_API_KEY, WORLD_MODEL_EXTRACTION_MODEL, WORLD_MODEL_REASONING_MODEL

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "world-model": {
      "command": "uvx",
      "args": [
        "world-model-mcp"
      ],
      "env": {
        "WORLD_MODEL_DB_PATH": "your-value",
        "ANTHROPIC_API_KEY": "your-value",
        "WORLD_MODEL_EXTRACTION_MODEL": "your-value",
        "WORLD_MODEL_REASONING_MODEL": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add world-model --env WORLD_MODEL_DB_PATH=your-value --env ANTHROPIC_API_KEY=your-value --env WORLD_MODEL_EXTRACTION_MODEL=your-value --env WORLD_MODEL_REASONING_MODEL=your-value -- uvx world-model-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "world-model": {
      "command": "uvx",
      "args": [
        "world-model-mcp"
      ],
      "env": {
        "WORLD_MODEL_DB_PATH": "your-value",
        "ANTHROPIC_API_KEY": "your-value",
        "WORLD_MODEL_EXTRACTION_MODEL": "your-value",
        "WORLD_MODEL_REASONING_MODEL": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "world-model": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "world-model-mcp"
      ],
      "env": {
        "WORLD_MODEL_DB_PATH": "your-value",
        "ANTHROPIC_API_KEY": "your-value",
        "WORLD_MODEL_EXTRACTION_MODEL": "your-value",
        "WORLD_MODEL_REASONING_MODEL": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • WORLD_MODEL_DB_PATH env
    Database location
  • ANTHROPIC_API_KEY 机密 env
    Optional - enables LLM-powered entity extraction
  • WORLD_MODEL_EXTRACTION_MODEL env
    Model for entity extraction
  • WORLD_MODEL_REASONING_MODEL env
    Model for complex reasoning

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 SaravananJaichandar 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 5787 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5787 个服务器的 24% 更新
  • 基础检查结果等于或优于此分类中其他 5787 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

World Model MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:ANTHROPIC_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.15.5)于4个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

Up-to-date docs for AI agents

作者:upstash广泛使用↓ 97.3万/周★ 6.4万今天更新

电脑或云端

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

作者:DeusData广泛使用↓ 1.8万/周★ 4.8万23天前更新

在你的电脑上运行

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

作者:exa-labs广泛使用★ 52132个月前更新

在云端运行✓ exa.ai

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

World Model MCP

Persistent memory + optional signed audit for AI coding agents.

world-model-mcp is persistent memory plus a post-quantum-signed, offline-verifiable audit trail for AI coding agents (FIPS 205 hybrid Ed25519 + SLH-DSA), MIT-licensed and fully local.

world-model-mcp ships a local SQLite knowledge graph your agent queries every turn: hallucinations become verifiable, corrections stick across sessions, and regressions get caught before they land. Flip on the audit chain and every event is signed with FIPS 205 hybrid Ed25519 + SLH-DSA, verifiable offline forever. MIT-licensed, runs entirely local, works with 10+ AI coding agents including Claude Code, Cursor, Codex, Continue, Cline, Windsurf, GitHub Copilot Chat, pi, OpenClaw, and Hermes Agent.

Latest: v0.16.3. Metadata refresh. No code changes. The PyPI summary and keyword set now name both artifacts that ship in this wheel: the MCP world-model memory server for coding agents, and the etch-verify offline audit-chain verifier CLI. Both were already installed by every prior release; the metadata is now honest about that so a searcher looking for an offline audit-chain verifier can find the package. v0.16.2 shipped CI hardening plus the world-model demo live notary beat introduced in v0.16.0 (three sample decisions signed into a real hybrid-signed epoch, verified VALID, mutated one byte to prove tamper detection fires live, then restored). Full version history in CHANGELOG.md.

Try it in 10 seconds

pip install -U world-model-mcp && world-model demo

You will see three sample decisions signed into a tamper-evident epoch, then the demo mutates one byte and re-verifies to prove the tamper is detected instantly (INVALID), then restores and re-verifies (VALID again). Offline, no account, no network. A world-model-demo-receipt.json lands in your current directory and a shareable etch.systems/verify#… URL is printed for anyone to check the same receipt in a browser.

mcp-name: io.github.SaravananJaichandar/world-model-mcp


Prefer a managed hosted version?

If you want the same signed audit chain without running the OSS server yourself, etch.systems ships a managed variant that uses this package as its offline reference verifier.

  • No infrastructure to run (POST your first event in 30 seconds, no signup)
  • Compliance framework mapping to SR 11-7, EU AI Act Article 12, ISO 42001, NIST AI RMF, SOC 2 CC7
  • External anchoring shipped end-to-end (Sigstore Rekor + Bitcoin OpenTimestamps)
  • Portable per-agent identity with key rotation and delegation across MCP client tools (Claude Code, Cursor, Continue, Cline, Codex)
  • Offline verifier stays the same: pip install world-model-mcp && etch-verify manifest.json verifies the hosted chain against pinned public keys without depending on the hosted service being online
curl -X POST https://etch.systems/v1/your-project

Returns a bearer token and an MCP endpoint you can point any MCP-compatible client at. Full docs at etch.systems.


FAQ

What is world-model-mcp? world-model-mcp is persistent memory plus a post-quantum-signed, offline-verifiable audit trail for AI coding agents, exposed as an MCP server the agent queries every turn. It runs entirely local, ships as MIT-licensed Python + optional adapters for 10+ AI coding agents.

How is it different from Mem0, Letta, and other agent-memory tools? world-model-mcp is the only agent-memory tool that ships a hybrid post-quantum signed audit chain (FIPS 205 Ed25519 + SLH-DSA-SHA2-128f) alongside memory, with an offline reference verifier (etch-verify) and dual external anchoring (Sigstore Rekor + Bitcoin OpenTimestamps) available via the hosted etch.systems companion. Peer tools (Mem0, Letta, agentmemory) ship memory without a signed audit chain. See the "Compared to" table below for a per-mechanism breakdown.

Is the audit trail post-quantum secure? Yes. Every closed epoch carries a hybrid signature: Ed25519 (classical) plus SLH-DSA-SHA2-128f (FIPS 205 stateless hash-based post-quantum signature). A future quantum adversary that breaks Ed25519 alone still faces the SLH-DSA signature over the same payload; both signatures must forge for the chain to be forged.

How do I verify a record offline, with no account? Run pip install -U world-model-mcp && world-model demo. The demo signs three sample decisions into a real hybrid-signed epoch, exports the same manifest format the etch-verify CLI reads, verifies VALID, mutates one byte to prove tamper detection is live (INVALID), then restores and re-verifies. A world-model-demo-receipt.json lands in your current directory and a etch.systems/verify#… URL is printed for anyone to check the receipt in a browser. Zero signup, zero network.

Which AI coding agents does it work with? Claude Code, Cursor, Codex, Continue, Cline, Windsurf, GitHub Copilot Chat, pi, OpenClaw, and Hermes Agent. Each has a dedicated starter repo under github.com/SaravananJaichandar/world-model-mcp- -starter. The MCP wire format is standard, so any MCP-capable client can consume the same tools.

Should I use this OSS package or the hosted etch.systems service? Use this OSS package (MIT-licensed, fully local) if you want to run the audit chain on your own infrastructure or add signed memory to an internal tool. Use etch.systems if you want the same audit chain shipped as a managed service with compliance framework mapping (SR 11-7, EU AI Act Article 12, ISO 42001, NIST AI RMF, SOC 2 CC7) and portable per-agent identity across MCP client tools. The offline reference verifier is the same in both cases: pip install world-model-mcp && etch-verify manifest.json verifies either an OSS-generated or a hosted-generated manifest against pinned public keys.


Compared to other agent-memory + agent-audit projects

Head-to-head positioning against eight named peers on the audit / signing / anchoring dimensions the agent-memory space is converging on. Every world-model-mcp cell carries a provenance flag: own = measured / observed in the shipped product; cited = pulled from the competitor's own public landing, repo, or press.

Source of truth for this table lives in the hosted service repo: world-model-mcp-hosted/src/etch/competitor_matrix.py. Update in both places if you change either.

world-model-mcp (this repo) + Etch (hosted)Mem0LettaagentmemoryUnicity AOSRepowiseTrinititeCauraFailproofAI
Signature schemeEd25519 + SLH-DSA-SHA2-128f (hybrid) [own]None (encryption at rest only)NoneNoneBLAKE3 hash-chainDeterministic signals (no signing)Signed + hash-chained (algo not disclosed)NoneNone disclosed
Post-quantum readyYes (SLH-DSA, NIST FIPS 205) [own]NoNoNoNo (BLAKE3 hash only)NoNo disclosedNoNo
Offline reference verifieretch-verify CLI, streaming, ships with PyPI package [own]NoNoNoNot disclosedNo (SaaS-only)Browser-based verifierNoNo
Attestation cadence enforcementScheduled systemd timer + on-demand verify [own]NoNoNoNot disclosedNoScheduled attestation runsNoNo
Framework mapping (Article / control IDs)EU AI Act Art. 12-15, SOC 2 CC6.6/7.2/7.3, ISO 27001 A.12.4/A.14.2 [own]SOC 2 + HIPAA (badges, no per-control mapping)Not disclosedNoNot disclosedEU AI Act (negative-space claim)Per-Article citations (EU AI Act, SOC 2, SR 11-7)SOC 2 in-progress badgeSOC 2 enterprise tier only
Drift detectionPer-epoch chain integrity + attestation trend [own]NoSuccess-rate + error trackingNoNot disclosedCode-health score deltasDeterministic replay + risk-score deltasNoEvaluator score deltas
Annotation support (signed human notes in-chain)pin_annotation MCP tool, signed into same chain [own]NoNoNoNot disclosedNoNot disclosedNoNo
Browser verifierYes, chain-integrity widget on /auditor/<slug> [own]NoNoNoNot disclosedNoYesNoNo
Share link (auditor access, no login)Yes, expiring share tokens (bs_ prefix, 30d max) [own]NoNoNoNot disclosedNoYes, expiring auditor accessNoNo
External anchor (independent witness log)Dual: Sigstore Rekor + Bitcoin OpenTimestamps (public, opt-out per project) [own]NoNoNoInternal hash-chain only (no external log)NoNot disclosedNoNo
OSS licenseMIT (world-model-mcp) [own]Apache 2.0Apache 2.0Apache 2.0Not disclosedAGPL v3 (core)No OSSApache 2.0No OSS
GitHub starsSnapshot via etch.systems/api/oss-stats [cited]61.6k [cited]23.9k [cited]24.9k [cited]7.1k [cited]4.2k [cited]No public repo373 [cited]No public repo
Public fundingBootstrapped [own]$24.5M [cited]$10M [cited]Not disclosed$3M seed Feb 2026 [cited]Not disclosedNot disclosedNot disclosedNot disclosed
Compliance posture (as claimed on landing)SOC 2 Type I in progress (Aug 2026 target) [own]SOC 2 + HIPAA (badges on trust subdomain)Not disclosedNo compliance postureNo compliance postureNo SOC 2; EU AI Act negative-space claimPer-Article compliance framingSOC 2 in-progress badgeSOC 2 enterprise-tier

How to read this table:

  • Bold cells describe mechanisms shipped in this repo (OSS) or the hosted service (etch.systems).
  • Peer cells are cited from each competitor's public landing / repo / press. Not our own measurement.
  • [own] on a world-model-mcp cell means we measured / observed the mechanism ourselves. [cited] means the value came from a third-party source.
  • Only the audit / signing / anchoring dimensions are in this table. General memory features (retrieval accuracy, adapter breadth, LLM support) are covered in the Features section below.

Numbers

BenchmarkScoreDetails
SWE-bench Verified repeat-mistake+10.2 points as a single-trial upper bound (67.3% → 77.6% on 49 paired instances); the multi-seed mean effect is +0.24 per instance, 95% CI [0, 0.47]Pre-registered, Claude Code 2.1.177 headless, Zenodo DOI 10.5281/zenodo.21076824. Within-domain +15.0 pts, cross-domain +6.9 pts with zero regressions on the single-trial split.
Contradiction-resolution100.0% on auto strategy105 pairs × 19 categories, deterministic (no LLM). Shipped since v0.11.0.
Coach-Player verification100.0% exact match12 hand-labeled pairs (4 grounded, 4 partial, 4 hallucinated). Layer 3 adversarial verification via independent Coach LLM. Shipped since v0.12.12.

The SWE-bench number is the load-bearing empirical claim. The other two are internal correctn

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