World Model MCP

Name: World Model MCP
Author: SaravananJaichandar

by SaravananJaichandarversion 0.15.5i★ –iRuns on your computer

Registry nameio.github.SaravananJaichandar/world-model-mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 87/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: ANTHROPIC_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: WORLD_MODEL_DB_PATH, ANTHROPIC_API_KEY, WORLD_MODEL_EXTRACTION_MODEL, WORLD_MODEL_REASONING_MODEL

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into 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"
      }
    }
  }
}

Run this in your terminal

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

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

WORLD_MODEL_DB_PATH env
Database location
ANTHROPIC_API_KEY secret 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

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account SaravananJaichandar, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 5760 servers in this category
Published to the registry more recently than 25% of the other 5760 servers in this category
Basic checks equal to or better than 100% of the other 5760 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is World Model MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: ANTHROPIC_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.15.5) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 972.7K/wk★ 64.2KUpdated 3 days ago

Computer or cloud

Install

Codebase Memory

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

by DeusDataWidely used↓ 18K/wk★ 48.1KUpdated 23 days ago

Runs on your computer

Install

Exa

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

by exa-labsWidely used★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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)	Mem0	Letta	agentmemory	Unicity AOS	Repowise	Trinitite	Caura	FailproofAI
Signature scheme	Ed25519 + SLH-DSA-SHA2-128f (hybrid) `[own]`	None (encryption at rest only)	None	None	BLAKE3 hash-chain	Deterministic signals (no signing)	Signed + hash-chained (algo not disclosed)	None	None disclosed
Post-quantum ready	Yes (SLH-DSA, NIST FIPS 205) `[own]`	No	No	No	No (BLAKE3 hash only)	No	No disclosed	No	No
Offline reference verifier	etch-verify CLI, streaming, ships with PyPI package `[own]`	No	No	No	Not disclosed	No (SaaS-only)	Browser-based verifier	No	No
Attestation cadence enforcement	Scheduled systemd timer + on-demand verify `[own]`	No	No	No	Not disclosed	No	Scheduled attestation runs	No	No
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 disclosed	No	Not disclosed	EU AI Act (negative-space claim)	Per-Article citations (EU AI Act, SOC 2, SR 11-7)	SOC 2 in-progress badge	SOC 2 enterprise tier only
Drift detection	Per-epoch chain integrity + attestation trend `[own]`	No	Success-rate + error tracking	No	Not disclosed	Code-health score deltas	Deterministic replay + risk-score deltas	No	Evaluator score deltas
Annotation support (signed human notes in-chain)	pin_annotation MCP tool, signed into same chain `[own]`	No	No	No	Not disclosed	No	Not disclosed	No	No
Browser verifier	Yes, chain-integrity widget on /auditor/<slug> `[own]`	No	No	No	Not disclosed	No	Yes	No	No
Share link (auditor access, no login)	Yes, expiring share tokens (bs_ prefix, 30d max) `[own]`	No	No	No	Not disclosed	No	Yes, expiring auditor access	No	No
External anchor (independent witness log)	Dual: Sigstore Rekor + Bitcoin OpenTimestamps (public, opt-out per project) `[own]`	No	No	No	Internal hash-chain only (no external log)	No	Not disclosed	No	No
OSS license	MIT (world-model-mcp) `[own]`	Apache 2.0	Apache 2.0	Apache 2.0	Not disclosed	AGPL v3 (core)	No OSS	Apache 2.0	No OSS
GitHub stars	Snapshot via etch.systems/api/oss-stats `[cited]`	61.6k `[cited]`	23.9k `[cited]`	24.9k `[cited]`	7.1k `[cited]`	4.2k `[cited]`	No public repo	373 `[cited]`	No public repo
Public funding	Bootstrapped `[own]`	$24.5M `[cited]`	$10M `[cited]`	Not disclosed	$3M seed Feb 2026 `[cited]`	Not disclosed	Not disclosed	Not disclosed	Not 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 disclosed	No compliance posture	No compliance posture	No SOC 2; EU AI Act negative-space claim	Per-Article compliance framing	SOC 2 in-progress badge	SOC 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

Benchmark	Score	Details
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-resolution	100.0% on `auto` strategy	105 pairs × 19 categories, deterministic (no LLM). Shipped since v0.11.0.
Coach-Player verification	100.0% exact match	12 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

Only the beginning is shown; read the rest in the repo

World Model MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

World Model MCP

Try it in 10 seconds

Prefer a managed hosted version?

FAQ

Compared to other agent-memory + agent-audit projects

Numbers