Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Self-hosted agent memory as a markdown vault: semantic and keyword search, wikilink graph, OAuth
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.
DATABASE_URL, VAULT_PATH, SECRET_KEY, MCP_HOSTNAME, EMBEDDING_PROVIDER, OLLAMA_URL, OPENAI_API_KEYAls 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": {
"obsidian": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DATABASE_URL",
"-e",
"VAULT_PATH",
"-e",
"SECRET_KEY",
"-e",
"MCP_HOSTNAME",
"-e",
"EMBEDDING_PROVIDER",
"-e",
"OLLAMA_URL",
"-e",
"OPENAI_API_KEY",
"ghcr.io/maxkuminov/obsidian-mcp:v1.1.0"
],
"env": {
"DATABASE_URL": "your-value",
"VAULT_PATH": "your-value",
"SECRET_KEY": "your-value",
"MCP_HOSTNAME": "your-value",
"EMBEDDING_PROVIDER": "your-value",
"OLLAMA_URL": "your-value",
"OPENAI_API_KEY": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add obsidian --env DATABASE_URL=your-value --env VAULT_PATH=your-value --env SECRET_KEY=your-value --env MCP_HOSTNAME=your-value --env EMBEDDING_PROVIDER=your-value --env OLLAMA_URL=your-value --env OPENAI_API_KEY=your-value -- docker run -i --rm -e DATABASE_URL -e VAULT_PATH -e SECRET_KEY -e MCP_HOSTNAME -e EMBEDDING_PROVIDER -e OLLAMA_URL -e OPENAI_API_KEY ghcr.io/maxkuminov/obsidian-mcp:v1.1.0Trag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"obsidian": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DATABASE_URL",
"-e",
"VAULT_PATH",
"-e",
"SECRET_KEY",
"-e",
"MCP_HOSTNAME",
"-e",
"EMBEDDING_PROVIDER",
"-e",
"OLLAMA_URL",
"-e",
"OPENAI_API_KEY",
"ghcr.io/maxkuminov/obsidian-mcp:v1.1.0"
],
"env": {
"DATABASE_URL": "your-value",
"VAULT_PATH": "your-value",
"SECRET_KEY": "your-value",
"MCP_HOSTNAME": "your-value",
"EMBEDDING_PROVIDER": "your-value",
"OLLAMA_URL": "your-value",
"OPENAI_API_KEY": "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": {
"obsidian": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DATABASE_URL",
"-e",
"VAULT_PATH",
"-e",
"SECRET_KEY",
"-e",
"MCP_HOSTNAME",
"-e",
"EMBEDDING_PROVIDER",
"-e",
"OLLAMA_URL",
"-e",
"OPENAI_API_KEY",
"ghcr.io/maxkuminov/obsidian-mcp:v1.1.0"
],
"env": {
"DATABASE_URL": "your-value",
"VAULT_PATH": "your-value",
"SECRET_KEY": "your-value",
"MCP_HOSTNAME": "your-value",
"EMBEDDING_PROVIDER": "your-value",
"OLLAMA_URL": "your-value",
"OPENAI_API_KEY": "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.
EMBEDDING_PROVIDER envOLLAMA_URL 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 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto maxkuminov 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: DATABASE_URL, VAULT_PATH, SECRET_KEY, MCP_HOSTNAME, OPENAI_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 (1.1.0) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Docker 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.
Your agents' memory, in the vault you already have, reachable from claude.ai, ChatGPT, Claude Code and your phone.
A self-hosted Model Context Protocol server over an Obsidian vault. Three things it does that the alternatives mostly don't:
expected_hash preconditions refuse an edit made from a stale read, every publish is atomic and no-clobber by default, deletes go to .trash/, and dry_run returns the diff before anything lands.Connect from Claude Code:
claude mcp add obsidian --transport http \
--url "https://obsidian-mcp. /mcp" \ --header "Authorization: Bearer omcp_..."
In claude.ai, Claude Desktop or ChatGPT, add a custom connector at https://obsidian-mcp. /mcp and sign in through the OAuth consent page. Connect a client has the rest.
Stack: Python 3.12, FastAPI, PostgreSQL with pgvector. Pluggable embeddings (Ollama — bge-m3 by default, qwen3-embedding:0.6b in the reference deployment — or OpenAI text-embedding-3-{small,large}).
There are three things going on here, and they're more interesting together than apart.
If you let an agent run for a while, it needs memory. Most setups solve this with an opaque vector store, a SQLite blob, or a managed "memory" service that you can't see into. That works until you want to know what the agent thinks it knows about you, or you need to correct something, or you want to understand why it just made a weird suggestion.
This server gives you a different deal. Agent memory lives as markdown files in your vault. Folder structure, file names, frontmatter, all visible. You can open the file in Obsidian and read it. You can edit it. You can delete it. You can grep it. The agent's "memory" is a human-auditable artifact that sits in the same place as your own notes, with the same tools available.
The home lab is the use case that sold me on this. My vault has notes on the rack, the network, and every Home Assistant integration. I can say "set up a night-light mode in the master bathroom, 1% after 11pm" and a sysadmin agent finds the right config, makes the change, and updates the doc in the same pass. Six months later when I've forgotten how it works, the answer is in the vault, not buried in some chat history I can't search.
The semantic search and wikilink graph still work over that material, so retrieval is fast and conceptual. But the substrate is files you own, not a black box.
To be precise about the scope: what the server supplies is MCP-accessible storage, keyword and semantic search, and graph operations over markdown notes, for whatever MCP clients you connect. The agents direct their own reads and writes. There is no extraction or decay pipeline running behind them, and nothing rewrites a note because a model judged it stale: an agent remembers something because it wrote a note, and forgets it because someone deleted one. By late 2026 that is less of a contrarian position than it sounds. Every vendor's consolidation step (the "dreaming" or "sleep-time" job) has turned into a separate process you can inspect, rather than silent extraction inside the write path. This server keeps the agent as the author. The consolidation help it will grow is a hygiene report that proposes merges and flags duplicates, and never writes (#359), not a pipeline that edits your notes while you are not looking.
The other half runs the other way: the vault isn't only the agents' memory, it's mine. I think of my Obsidian vault as my exocortex. The "big me" that includes notes, calendars, scripts, search, and AI assistants is substantially more capable than the "small me" of the biological brain alone. It's also where I do most of my thinking, because writing something down is itself a form of thought.
The problem is that until recently, the vault was passive. I had to go find things. Agents that wanted to help me had to be briefed from scratch every session, and they had no way to see what I'd already written about a topic.
This server fixes that. Now the same vault feeds my own daily writing and any agent I plug into it. The agent reads what I read, links what I link, follows the same wikilinks, sees the same frontmatter. When I write a project note on Sunday, my Monday-morning briefing agent already knows about it. When the agent leaves notes from a research session, they show up in my normal Obsidian search.
A concrete version of this: I'll spend a session in Claude Code on a project, wrap up, push the commits, and then just say "update Obsidian." The agent reads the vault guide, figures out where project notes live in my structure, picks the right format and frontmatter, and leaves a session log I can later roll into a status report. No path-passing, no telling it what to write — the conventions are already in the vault, and it follows them.
That's the exocortex idea made concrete: one place that holds context, and both the human and the agents reading and writing into it on the same terms.
The thing that still surprises me is that this is internet-facing. Same vault, same notes, reachable from anywhere I happen to be talking to an agent — Claude in a browser tab, Claude on my phone on the train, an n8n workflow firing on a schedule, a Claude Code session on whatever laptop is in front of me. All behind OAuth or a bearer key, all hitting the same source of truth.
So when I hear an interesting podcast on a commute and want to think out loud about it with Claude on my phone, the agent isn't starting cold. It can pull up what I've already written on adjacent topics, surface a note I half-finished six months ago, and at the end of the conversation suggest updates and write them in. The vault doesn't have to be near me to be the thing I'm working in. (A session away from the keyboard walks through exactly one of these.)
To make the abstract concrete, a short transcript from a real session. Tool calls inline; the user types in plain English and the agent picks the right tool.
you > find anything I've written about why retrieval-augmented
chat is hard
claude → semantic_search(query="why retrieval-augmented chat is hard") • 2025-12-03 - RAG failure modes.md • 2025-10-18 - Chunking tradeoffs.md • 2024-06-22 - Vector recall vs precision.md
the closest hit is your December note on RAG failure modes. let me see what it's connected to.
→ get_neighborhood(path="2025-12-03 - RAG failure modes.md", depth=1) 8 connected notes. notable ones: • "Hybrid search" — a re-ranking design you sketched but didn't ship • "Out-of-distribution queries" — a half-finished draft from October • "Embedding model choice" — links to bge-m3, your current model
you have three connected pieces here: a failure-modes catalog, an unshipped hybrid-search sketch, and an abandoned O-O-D draft. want me to summarize all three together, or pull up the draft so you can decide whether to finish it?
you > pull up the draft, and tag it #revisit-2026 in frontmatter while you're there
claude → read_note(path="2025-10-18 - OOD queries (draft).md") → set_frontmatter( path="2025-10-18 - OOD queries (draft).md", updates={"tags": ["draft", "rag", "revisit-2026"]} )
here's the draft, and the tag is on. you stopped right before the section on confidence thresholds; the open question you left yourself was…
Two things to notice. First, the agent didn't need to be told what folder to look in or what tools to use — it picked them. Second, the write at the end is structured (set_frontmatter mutating YAML, not a regex over the file body), so the note round-trips cleanly. The self-describing vault and the wikilink graph are doing the work that makes this feel natural.
The transcript above is the easy case: I'm at a desk, I can see what the agent is doing, and Obsidian is one alt-tab away. The session that actually changed how I think about this server had none of that.
I was out walking with a health podcast in my ears — a long one, two people who clearly disagreed with each other, an hour of it. I had my phone and no intention of going home to a laptop. So I pulled the episode's transcript, handed it to Claude on my phone, and we talked it through while I kept walking: what the actual claim was, which parts I already had notes on, where it cut against something I'd decided months ago and written down at the time.
The agent had the vault the whole way. It surfaced what I'd already written on the topic, flagged that two dates in an older note were wrong, and asked whether a decision I'd recorded last year still stood given what the episode argued. By the time I got back it had written all of it in: the health-related decisions I'd actually landed on during the walk, the date corrections in the old note, a couple of new notes on the episode itself — and, because the conversation kept circling back to it, a durable note on how I decide which experts to trust on medical questions in the first place. That last one is the artifact I keep returning to. It wasn't about the episode at all; it was the reasoning underneath a whole class of decisions, and it now sits in the vault where the next agent will find it.
I never opened Obsidian. Not on the walk, not when I got home. The whole session — retrieval, argument, correction, and the writing that came out of it — went through an agent, and the vault is simply where it landed. Obsidian is how I check the w
Nur der Anfang wird gezeigt; den Rest findest du im Repo