Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Local-first agent memory that preserves what happened, when and why
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.
KMP_MCP_DATA_DIR, KMP_VIEWER_ADDR, KMP_KERNEL_GRPC_ENDPOINTWelche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
Trag die leeren Werte ein, bevor du ihn startest.
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.
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.
KMP_MCP_DATA_DIR envKMP_VIEWER_ADDR envKMP_KERNEL_GRPC_ENDPOINT 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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto underpass-ai 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.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
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 (0.24.0) kam vor 40 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du MCPB, Rust 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
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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.
KMP — Agent memory that remembers why
Local first. Evidence attached. Time included.
KMP is local-first memory for coding agents. It runs beside Codex, Claude Code and Hermes Agent as one small binary with an embedded SQLite store, and it remembers what was decided, what the evidence was and when it happened. Never the transcript. No account, no service, no API key: memory stays on your machine.
Ask your agent "Why did we choose SQLite?" and it answers from stored evidence, or says UNKNOWN instead of guessing. Ask "Show me the memory behind this decision" and ChronoLoom, the viewer that ships inside the binary, opens on that decision and lights up its proof path, with time as a dimension you can move through and a view the agent and you steer together. Memory tools retrieve and audit the evidence, view tools steer that shared ChronoLoom view, and the running server's tools/list defines the current surface.
Your agent decides something today. Tomorrow a new session, or a different agent, rediscovers the same incident from scratch, or quietly contradicts the decision because the reason for it was in a context window that is gone. Summaries lose the reason; transcripts bury it.
KMP keeps the decision, the evidence it rested on and the moment it happened, as a typed, temporal memory the next session asks instead of re-deriving:
UNKNOWN is an honest answer when the evidence is not there.Install KMP in your host (below), then in any project:
kmp-mcp demo
It writes a worked example into that project's memory — a checkout service, an incident, the decision that replaced an earlier one and the measurement that verified it — opens ChronoLoom on it and prints the questions to ask:
| You say | You get |
|---|---|
| "Why are retries to the payment provider capped at two?" | The decision, with the incident and the ADR it cites. |
| "What did we believe about retries in August 2026?" | The earlier decision, as it stood then, not the cap that replaced it. |
| "What changed about retries in September 2026?" | The incident, the cap and the measurement, in order. |
| "Show me the memory behind the retry cap decision." | ChronoLoom opens on the decision and lights up its proof path. |
Name KMP and the about example:kmp-demo in the request. The example never enters your project's committed bundle. More examples, including KMP's own memory.
Install the plugin, run setup, restart the host once. The guides reach a fresh store on the first read; nothing else to run.
/plugin marketplace add underpass-ai/kmp@marketplace
/plugin install kmp@underpass /kmp:setup
codex plugin marketplace add underpass-ai/kmp --ref marketplace
codex plugin add kmp@underpass
Then ask Codex to run kmp-setup.
With kmp-mcp installed, register it and install the skills through the native lifecycle:
kmp-mcp setup --hermes
kmp-mcp doctor
or run /kmp:doctor. The plugin owns the MCP registration, so do not add a second KMP server by hand. cargo install kmp-mcp --locked is the fallback for a platform with no published engine; MCPB packages, release tarballs and the Pi coding agent are covered in the plugin installation guide. Store selection and repair live in Embedded KMP.
You normally ask for the outcome. The KMP skill chooses the memory moves.
| You say | The agent does | You get |
|---|---|---|
| "Continue the KMP documentation work." | Wakes project:kmp before re-deriving it. | Current decisions, constraints and next actions. |
| "Why did we choose SQLite?" | Asks memory and follows the stored evidence. | A grounded answer, or UNKNOWN. |
| "What does KMP remember from yesterday?" | Resolves the interval and navigates every temporal page. | Ordered memory from that period. |
| "Why was the launch postponed in March?" | Asks memory standing within March: only what fell inside competes, and the lifecycles are read as they stood then. | A grounded answer from that time, or UNKNOWN naming the nearest match outside the span. |
| "Remember that retries are capped at two because logs showed amplification." | Records the decision, its evidence and meaningful relations. | Durable state with an auditable why. |
| "Show the proof between this incident and that decision." | Traces the typed path and inspects its evidence. | The stored connection, rationale and sources. |
| "Undo that decision." | Writes a state that supersedes the old one. | Both decisions remain visible in time. |
| "Save the project memory." | Exports the maintained project bundle and shows its diff. | Reviewable .kmp/memory.jsonl. |
KMP is memory, not surveillance. Store durable decisions and evidence, not transcripts.
It also waits to be asked. A session that never mentions memory makes no KMP call at all. Naming KMP, running a /kmp:* command, or opting in from your project's CLAUDE.md or AGENTS.md is what opens a route. If you would rather it enter known work on its own:
kmp-mcp config memory-routing always
kmp-mcp config memory-routing on-request # the default
Ask in any language. The stored evidence is never translated; the answer comes back in yours. How that works.
flowchart LR
U[You] --> H[Codex or Claude] H --> S[KMP skill] S -->|chooses a move| M[kmp-mcp] M --> K[embedded kernel] K --> D[(.kernel/\nSQLite)] K --> V[local read-only viewer]
The plugin installs the skills and declares one local MCP process. The skill turns intent into one or more typed tools. kmp-mcp validates the request, and the kernel reads or writes the local graph-temporal store. The agent, not KMP, turns returned evidence into conversational prose.
| Layer | Owns | Does not own |
|---|---|---|
| Plugin | Installation, host discovery, skills and the single MCP declaration. | Memory semantics or a second tool vocabulary. |
| Skills | When to recover, ask, navigate, audit, write, diagnose, save or restore. | Persistence. |
| kmp‑mcp | The schema-checked tool boundary over local stdio. | Choosing a workflow from user prose. |
| Kernel | Validation, temporal storage, traversal, deterministic retrieval and proof. | Generating prose or inventing rationale. |
Explore ChronoLoom · Technical architecture
| Boundary | Default behavior |
|---|---|
| Memory | Stored on your machine, normally in the repository's .kernel/. |
| MCP transport | Local stdio between the agent host and kmp-mcp. |
| Viewer | Read-only loopback HTTP, normally rooted at http://127.0.0.1:7317/, behind a random per-session capability. |
| External services | None required; optional TypeSafe Jev integrations send selected text to the configured service. |
| Underpass | Receives no memory and operates no service in this path. |
| Updates | Setup and updates contact GitHub Releases for checksummed packages; the Claude session hook can check releases daily. |
| Local metadata | Agent identities and guide delivery records live outside memory retrieval; quality diagnostics use a separate local journal. |
| Cloud agents | Evidence returned to a cloud agent follows that host's data policy. |
.kernel/ is machine state and is ignored by git. A project-scoped store also maintains .kmp/memory.jsonl. Export and Git commit are local operations; pushing, syncing or sharing the bundle makes its contents available elsewhere. Review its diff before sharing. Evidence read by the agent is also subject to the host's data policy, independently of whether you share the bundle.
This repository eats its own cooking. .kmp/memory.jsonl is the memory of why KMP is the way it is: the decisions behind it, each with the document that states it, and the ones that superseded older ones. Restore it with /kmp:restore and ask "why does a release advance the marketplace branch last?" How it is written.
Several machines can share one live KMP service through the Kubernetes topology backed by Neo4j, Valkey and NATS JetStream. It is still free, open source and self-operated. "Enterprise" describes the operational shape, not a paid tier or an Underpass-hosted product. It also means owning infrastructure, TLS, identity, authorization and observability. Keep it local until those responsibilities buy you something. Then read Enterprise KMP.
KMP is pre-1.0: useful today, actively evolving, and explicit about sharp edges. Release automation builds kmp-mcp for Linux x86_64/arm64, macOS arm64/x86_64 and Windows x86_64. The embedded path is the default; the remote API is versioned v1beta1 and expects an operator.
We do not paste old benchmark numbers into the README. Reproducible, current evidence belongs in Research before it becomes a claim.
Not in the default embedded setup. The process, store and viewer are local. The agent host may be cloud-backed, so evidence sent to that agent follows the host's policy.
No. The shipped embedded binary uses SQLite. Kubernetes is only for a shared service.
No generative model is required for the default embedded path. KMP validates, stores and retrieves evidence; your agent writes the final answer and the English search summary. Optional TypeSafe Jev features send selected text to an external model for judgments, and optional semantic retrieval uses a local encoder. These integrations require explicit configuration. See retrieval defaults and opt-ins.
Yes: both speak the same MCP contract, and SQLite supports multiple local hosts. Use the maintained project bundle to move state between machines, or the enterprise topology for shared network access.
UNKNOWN an error?No. It means the selected memory did not contain eligible evidence for the question. That is safer than a confident invention.
Run the host's kmp-doctor workflow and follow the missing-tools runbook. The usual suspects are a stale host session, duplicate MCP ownership, a missing binary or an unsupported store format.
No.
Nur der Anfang wird gezeigt; den Rest findest du im Repo