
Dakera Mcp
io.github.Dakera-AI由 GitHub 账号 Dakera-AI 发布v0.12.3更新于 Oct 27, 2026
Agent memory engine — 106 MCP tools, self-hosted, single Rust binary
概览
为 AI 助手提供持久、可检索记忆的 MCP 服务器,后端为自托管的 Dakera 实例,默认加载 14 个工具,可按需扩展。
- 可以做什么
- 按语义查询、标签、类型或向量加全文混合方式存储、召回与搜索记忆
- 按会话和代理组织记忆,并按标签、类型或时间范围批量召回或批量删除
- 从种子记忆构建知识图谱,并从自由文本中抽取实体与结构
- 把文档导入为带引用的分块记忆,并在服务器开启相应功能时管理附件、语音转写与图像索引
- 按需发现并加载更多工具定义,查询服务器健康状态、能力、加密与迁移状态
- 适用场景
- 适合需要助手跨会话记住信息、并对自身保存的笔记、文档或对话历史做语义检索的场景。也适合已运行或计划自托管 Dakera 记忆服务器、希望默认工具集精简、需要时再扩展的团队。
- 运行要求
- 需要一个可通过 HTTP 访问的 Dakera 记忆服务器(v0.11.108 或 v0.12.0 至 v0.12.3)以及 Dakera API 密钥。本地进程可通过 npm 包、Homebrew、Cargo、Docker 镜像或预编译二进制安装。配置使用 DAKERA_API_URL 与 DAKERA_API_KEY 环境变量,DAKERA_MCP_PROFILE 用于选择工具配置档。
安装
在 SourceWeft 中
- 打开 控制台中的 Dakera Mcp,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
⚡ dakera-mcp
[CI] [Crate] [npm] [Downloads] [License: MIT] [LoCoMo 88.2%] [Glama] [Docs] [dakera.ai] [Playground]
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
Architecture: 14 core tools + on-demand discovery
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:
- 14 tools loaded by default — the 12 highest-frequency memory operations + 2 meta-discovery tools
- On-demand expansion — use
dakera_discover_toolsanddakera_load_toolsto fetch additional tool schemas only when you need them
Default tool set (core profile)
Profiles & token cost
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).
Accessing additional tools
Profile selection
The profile controls which tools appear in tools/list. Three ways to set it:
1. Per-request (in tools/list params):
2. Environment variable (applies to all requests):
3. Default: core (14 tools, ~3,400 tokens)
Dakera v0.12
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.
New with Dakera v0.12.2
What is new
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:<hex> of an attachment in the agent's own namespace,
_dakera_agent_<agent_id>). 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.
Recall: top_k ranked results, context apart
dakera_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.
Documents (Dakera v0.12.3)
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):
A recall result that is a chunk carries citation: document_id, title, page_start /
page_end, heading_path, chunk_index / chunk_count (from memory.metadata._dakera_document).
On a server before v0.12.3 (no documents section in /v1/capabilities) the tools are not listed and
a direct call says they need v0.12.3; DAKERA_DOCUMENTS=0 on the server hides them the same way.
Features the server has off are left out
The opt-in features (attachments, speech to text, image indexing) are off by default on the server.
dakera-mcp asks GET /v1/capabilities (once a minute, 3 s timeout) before it lists tools:
attachmentsoff, or a server without/v1/capabilities(v0.11): thedakera_attachment_*tools are not listed and not returned bydakera_discover_tools; a direct call answers with the variable to set (DAKERA_ATTACHMENTS=1) and makes no request.visionoff:dakera_attachment_index_imageis left out (DAKERA_VISION=1turns it on).- A server without
/v1/capabilities(v0.11) also hidesdakera_encryption_statusanddakera_embed_migration_status, whose routes are new in v0.12. - The server cannot be asked (down, starting, key refused): nothing is hidden (asked again after 10 s).
The default core profile has no opt-in tools, so it never makes that request.
Errors
Error answers keep the server's text and add a Hint: line for the v0.12 cases: a key pinned to
namespaces gets 403 on node-wide /admin routes (backups, encryption, quotas, config); backup
download, upload and restore need super_admin; 413 (body over a limit, or a hard quota), 501
(feature off), 503 (Retry-After, which the retry logic now honours, up to 8 s) and 429 (rate
limit). A route the server lacks (an older server) and a v0.11 rotation without new_key get a hint
too. Since Dakera v0.12.2 a refused argument gets 400 with a message naming the field
(content: content exceeds maximum of 100000 bytes …, tags[1]: … reserved …); the message is
passed on and the hint names the field to correct (the content limit counts UTF-8 bytes). The 403
hints point at dakera_whoami. From Dakera v0.12.3 the admin key, backup and rotate-key
routes refuse a field they do not know (422); the hint names it. A request that timed out is retried only when it is safe to repeat (GET, PUT, DELETE): a store,
an import or a key rotation is never sent twice.
Run Dakera
The MCP server connects to a Dakera memory server. You need one running first:
For persistent storage (recommended):
Full deployment guide (Docker Compose, Kubernetes, Helm): dakera-deploy
Install
npm / npx (Node.js 18+)
Homebrew (macOS / Linux)
Cargo
Docker
The image is distroless (no shell, no package manager) and runs as the non-root user 65532.
Binary download
Pre-built binaries for macOS, Linux, and Windows are available on the releases page.
Connect
Add to .mcp.json (Claude Code) or claude_desktop_config.json (Claude Desktop):
dakera_extract_entities calls the ODE sidecar at DAKERA_ODE_URL; those requests currently carry
the Dakera API key as well (tracked in Dakera-AI/dakera#924).
To start with the power profile (exposes up to 86 tools):
Why This Exists
AI agents forget everything when the session ends. Dakera fixes that. This MCP server gives your agent a persistent memory layer with zero infrastructure overhead — point it at a Dakera instance and it works.
The 14-tool default keeps your context window lean. The meta-tools let you expand on demand when you need advanced operations like bulk vector upsert, knowledge graph traversal, or memory federation.
→ dakera.ai for hosted instance
→ Self-host with dakera-deploy
Documentation
Related
dakera.ai · Documentation · Request Early Access
Part of the Dakera AI open-core ecosystem. Built with Rust. Self-hosted. Zero dependencies.
来源:README.md,提交 70c9cc2
工具
0版本历史
5- v0.12.3最新Oct 22, 2026
- v0.12.2Oct 8, 2026
- v0.12.0Oct 5, 2026
- v0.11.0Oct 1, 2026
- v0.10.12Sep 16, 2026
评分
已满足适用检查项的 50%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
- 近 30 天内可连通25 分
请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。
- 已声明认证方式10 分
请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。
- 已列出工具15 分
请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。
- 描述必需15 分
- 图标10 分
- 文档15 分
- 许可证10 分