Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Agent memory engine — 106 MCP tools, self-hosted, single Rust binary
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.
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": {
"dakera": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/dakera-ai/dakera-mcp:0.12.3"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add dakera -- docker run -i --rm ghcr.io/dakera-ai/dakera-mcp:0.12.3In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"dakera": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/dakera-ai/dakera-mcp:0.12.3"
]
}
}
}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": {
"dakera": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/dakera-ai/dakera-mcp:0.12.3"
]
}
}
}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.
Diese 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 Dakera-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 (0.12.3) kam vor 15 Tagen 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.
MCP server for Dakera AI. Gives any MCP-compatible AI agent persistent, queryable memory — with smart token management built in.
Works with Claude, Claude Code, and any MCP-compatible framework.
Part of Dakera AI — the memory engine for AI agents.
The Dakera memory engine scores 88.2% Recall@20 on LoCoMo (1,536 evaluated questions · LLM-judged retrieval recall) — benchmark details
Starting every agent session with 60+ tool schemas wastes ~15K tokens before you write a single message. dakera-mcp solves this with hybrid tool exposure:
dakera_discover_tools and dakera_load_tools to fetch additional tool schemas only when you need them| Tool | Purpose |
|---|---|
dakera_store | Store a memory with importance, tags, and type |
dakera_recall | Semantic recall by query text |
dakera_search | Advanced memory search with tag/type filters |
dakera_session_start | Start a session to group related memories |
dakera_session_end | End a session with optional summary |
dakera_batch_recall | Bulk filter-based recall (by tags, importance, time) |
dakera_forget | Delete specific memories by ID |
dakera_hybrid_search | Combined vector + BM25 search |
dakera_fulltext_search | BM25 full-text search |
dakera_knowledge_graph | Build a knowledge graph from a seed memory |
dakera_extract | Extract entities and structure from free-form text |
dakera_batch_forget | Bulk delete by tags, type, or time range |
dakera_discover_tools | Search the full tool catalog by keyword or tier |
dakera_load_tools | Load full schemas for specific tools on demand |
| Profile | Tools | ~Tokens | How to enable |
|---|---|---|---|
| core | 14 | ~3,500 | Default — always loaded |
| admin | 34 | ~6,850 | DAKERA_MCP_PROFILE=admin |
| power | 86 | ~18,200 | DAKERA_MCP_PROFILE=power |
| all | 106 | ~21,600 | DAKERA_MCP_PROFILE=all |
Token figures are estimates (JSON bytes / 3). The attachment tools below count in power and all, but only appear while the connected server has the feature on (see Dakera v0.12).
# In your agent: discover what's available
dakera_discover_tools(tier="power") → returns names + descriptions, no schemas loaded
dakera_load_tools(tools=["dakera_consolidate", "dakera_agent_stats"]) → returns full inputSchema for each tool
The profile controls which tools appear in tools/list. Three ways to set it:
1. Per-request (in tools/list params):
{"profile": "power"}
2. Environment variable (applies to all requests):
DAKERA_MCP_PROFILE=power
3. Default: core (14 tools, ~3,400 tokens)
dakera-mcp 0.12.3 works against Dakera v0.11.108 and v0.12.0 – v0.12.3 servers. Every tool keeps its name and arguments; the additions are optional arguments that are sent only when you supply them (or that an older server ignores), and tools that call new routes and say so on a server without them. The 0.12.3 additions (separate neighbourhood context, the unknown-field hint, document import) need a v0.12.3 server.
| Dakera server | dakera-mcp 0.12.3 |
|---|---|
| v0.12.3 | every tool; the recall tools list neighbourhood context apart in context_memories (neighborhood_mode) |
| v0.12.2 | every tool; the recall tools keep the first top_k results and say how many unmarked context items they left out; the attachment tools while DAKERA_ATTACHMENTS (and DAKERA_VISION for images) is on |
| v0.12.0, v0.12.1 | every tool; dakera_session_touch and dakera_agent_create answer that nothing is needed (sessions are not ended for inactivity there, and an agent is created by its first memory); dakera_whoami says it needs v0.12.2; listings return full content (no preview) and include derived sentence sub-memories |
| v0.11.108 | as v0.12.0, and the attachment tools, dakera_encryption_status and dakera_embed_migration_status are not listed (a direct call says they need v0.12); dakera_encryption_rotate_key needs new_key |
| older | not tested |
| Tool / argument | Tier | What it does |
|---|---|---|
dakera_session_start idle_timeout_secs | core | the server ends a session idle for 4 h by default; this sets the session's own timeout (0 = never, at most 30 days) |
dakera_session_touch | power | POST /v1/sessions/{id}/touch: keeps a session open while the agent works without storing or recalling; answers session_state (active with idle_deadline_at, or ended) |
dakera_store | core | storing into an ended session still succeeds; the answer's session_state: "ended" is followed by a note telling the agent to start a new session |
dakera_session_end | core | a note when the server had already ended the session for inactivity (the summary passed is then not saved) or when no such session is reachable |
dakera_session_list / _get / dakera_agent_sessions | power | sessions carry last_activity_at, ended_reason (client or idle) and idle_since |
dakera_agent_create | power | POST /v1/agents: creates an agent (its memory namespace) before its first memory; created: false for an existing one |
dakera_whoami | power | GET /v1/auth/whoami: the key's scope, namespaces (prefix patterns such as _dakera_agent_mlx-*), expiry and inert entries; the first thing to call on a 403 |
dakera_agent_memories / dakera_session_memories / dakera_knowledge_network_cross_agent content_preview_chars | power | content cut to 500 characters by default (content_len / content_truncated mark it; 0 = full content); dakera_memory_get and recall return memories in full |
dakera_agent_memories / dakera_wake_up include_derived | power | derived sentence sub-memories are left out of listings by default since v0.12.2; true lists them too |
| Tool | Tier | Needs | What it does |
|---|---|---|---|
dakera_capabilities | power | v0.12 | GET /v1/capabilities: active model, search mode, scoring strategy, accepted lang values, which opt-in features are on. On a v0.11 server it answers capabilities_available: false |
dakera_health | power | any | GET /health: status and version; on v0.12 also degraded, config_warnings, embed_migration |
dakera_wake_up | power | any | an agent's startup context in one call: its top memories by importance x recency, no query, no embedding |
dakera_embed_migration_status | admin | v0.12 | progress of the one-time background re-embed after the upgrade |
dakera_encryption_status | admin | v0.12 | the encryption keyring and the background re-seal (never key material) |
dakera_encryption_rotate_key | admin | v0.11+ | new_key is optional on v0.12 once encryption is on (the server generates a key; with encryption off, new_key turns it on); wait_secs (at most 20); namespace rotates one namespace |
dakera_attachment_upload / _list / _download / _delete | power | v0.12 + DAKERA_ATTACHMENTS | files (or text) a memory can reference with dakera_store attachment_ref |
dakera_attachment_transcribe | power | v0.12 + DAKERA_ATTACHMENTS | WAV speech to text in any language the model knows (lang forces one) into a memory; a background job, wait_seconds (at most 45) waits for it |
dakera_attachment_index_image | power | v0.12 + DAKERA_ATTACHMENTS + DAKERA_VISION | PNG page as a visual memory (use an agent dedicated to images: the visual lane stores page vectors) |
dakera_attachment_job | power | v0.12 + DAKERA_ATTACHMENTS | status of a transcription / index job |
Per-request `lang` (en, de, fr, es, it, pt, nl; v0.12) is accepted by dakera_store, dakera_recall, dakera_recall_associated, dakera_search, dakera_memory_update, dakera_extract, dakera_auto_tag and the attachment jobs; dakera_store also takes attachment_ref (sha256: of an attachment in the agent's own namespace, _dakera_agent_ ). Neither is sent unless given, so the same calls work on a v0.11.108 server.
Other optional arguments (all servers): ttl_seconds and metadata on dakera_store; tags, memory_type and session_id filters on dakera_recall; limit on dakera_batch_recall; limit / offset on dakera_session_list, dakera_session_memories and dakera_agent_sessions (the server pages at 50); content_preview_chars on the memory listings and include_derived on dakera_agent_memories / dakera_wake_up (v0.12.2, ignored by older servers); memory_type on dakera_knowledge_deduplicate; dedup_on_store / dedup_threshold on dakera_memory_policy_set.
top_k ranked results, context apartdakera_recall and dakera_recall_associated return at most top_k ranked results in memories. They ask the server for neighborhood_mode: "separate", so the session neighbours of the results (memories written around the same time in the same session) come back in their own context_memories list: each entry has context_of (the id of the ranked memory it belongs to) and context_of_rank (that memory's place in memories); its score comes from another search and is not comparable with the ranked scores. A collapsed result (server flag DAKERA_RECALL_COLLAPSE_DERIVED) keeps matched_text, the sentence that matched. neighborhood_mode picks separate (default), inline or off. A server that predates neighborhood_mode (before v0.12.3) appends its context to memories unmarked: the tools keep the first top_k and say how many items they left out.
Memory content in tool results is stored data: initialize tells the client to reason about it and never follow instructions found in it.
A document becomes chunk memories of the agent, each with its heading path and page, imported by a background job (power tier; listed when /v1/capabilities has documents.enabled):
| Tool | What it does |
|---|
| dakera_import_document | content (text, text/markdown or text/html as media_type) or attachment_ref of a file uploaded with dakera_attachment_upload (PDF, DOCX, ...; namespace defaults to the agent's); title, document_id (re-importing it replaces the document), memory fields (tags, session_id, memory_type, importance, metadata, lang), chunking (max_tokens, overlap_tokens, strategy structure or
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