Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Temporal knowledge graph for codebases with constraint enforcement at the edit boundary.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
WORLD_MODEL_DB_PATH, ANTHROPIC_API_KEY, WORLD_MODEL_EXTRACTION_MODEL, WORLD_MODEL_REASONING_MODELAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"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"
}
}
}
}Führe das in deinem Terminal aus
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-mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"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"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"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"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
WORLD_MODEL_DB_PATH envWORLD_MODEL_EXTRACTION_MODEL envWORLD_MODEL_REASONING_MODEL envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 8. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto SaravananJaichandar bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: ANTHROPIC_API_KEY
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.15.5) kam vor 4 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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-verifyoffline 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 theworld-model demolive 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.
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
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.
pip install world-model-mcp && etch-verify manifest.json verifies the hosted chain against pinned public keys without depending on the hosted service being onlinecurl -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.
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.
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:
[own] on a world-model-mcp cell means we measured / observed the mechanism ourselves. [cited] means the value came from a third-party source.| 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
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