Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Memory your agent can trust — every answer carries its source; when it doesn't know, it says so.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 menot-you 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.2)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Your agent forgets everything between sessions. nMEMORY makes it remember, with sources.
curl --proto '=https' --tlsv1.2 -fsSL https://no.tt/install.sh | sh
Or install from source. You need uv and Git:
git clone https://github.com/menot-you/n-memory
cd n-memory uv sync uv run nmemory database create claude mcp add nmemory -- uv run --directory "$PWD" nmemory mcp serve
uv sync installs the pinned Python (3.14) and all dependencies. database create makes the store file. nMEMORY never makes it implicitly. Any MCP client that speaks stdio connects the same way as Claude Code.
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flowchart LR agent["Your agent (any MCP client)"] -->|"stdio, 18 tools"| server["nmemory mcp serve"] shell["You, in a shell"] -->|"nmemory CLI"| core server --> core["Capture and recall"] core -->|"one transaction per call"| store[("One SQLite file records, journal, index")] core -->|"BM25, always"| lexical["Keyword recall"] core -.->|"when a key is set"| vectors["Embedding provider"] lexical --> outcome{"grounded missing_evidence abstain"} vectors -.-> outcome
Each record must have a source and an anchor (path:line, a quote or a PR). Recall returns one of three outcomes. It never turns a weak match into an answer.
Counted on 2026-10-21. Tools: the MCP tools/list request to nmemory mcp serve. Tests: uv run --group dev pytest --collect-only -q in each member root.
| Before | With nMEMORY |
|---|---|
| Each new session starts empty. You explain the same decision again. | The agent recalls the decision at the start of the session. |
| A recalled "fact" has no origin. You cannot check it. | Each record must have a source and an anchor. |
| A weak match comes back as a confident answer. | Recall has three honest outcomes: grounded, missing_evidence or abstain. |
| Old notes and new notes conflict in silence. | A new record can supersede an old one. Every change goes into a hash-chained audit journal. |
| Text from a web page or a file can steer the agent. | nMEMORY marks imported or directive-shaped text as tainted. Recall labels all results as data, not instructions. |
Your agent uses the MCP tools. You can use the same store from the shell.
Store a decision (the agent calls nmemory_capsule_ingest):
{
"content": "We store data in SQLite, not PostgreSQL.", "kind": "decision", "source": "docs/adr/0001-storage.md", "anchor": "docs/adr/0001-storage.md:3" }
In a later session, recall it:
uv run nmemory capsule retrieve "what database stores our data"
uv run nmemory capsule show --id cap-1
The first command returns "outcome": "grounded" and the record. The second command shows its provenance: source, anchor and source hash.
NOTT_NMEMORY_EMBED_PROVIDER, also openai or openai-compatible for a self-hosted server such as Ollama or vLLM).GEMINI_API_KEY for the default), nMEMORY sends capsule text and queries to that provider. To keep recall lexical only, unset that key. No key is needed to start.A notes file (CLAUDE.md, AGENTS.md) | A plain vector store | nMEMORY | |
|---|---|---|---|
| Survives a new session | Yes | Yes | Yes |
| Source required per record | No | No | Yes |
| Says "no evidence" on a weak match | No | No, it returns the nearest vectors | Yes |
| Works with no embedding key | Yes | No | Yes (lexical) |
| Audit trail of each change | Git only | No | Hash-chained journal |
| Grows without filling the prompt | No, the whole file loads | Yes | Yes, recall has a token budget |
The evaluation harness holds runners for synthetic recall, LongMemEval and extraction. It publishes methods, not a score for this release. We do not quote older numbers here, because they measured an earlier engine.
Memory that cites its source.
Tracked, resumable agent workers.
The live web as cited evidence.
App Store Connect for agents.
The team contract, routes and hooks.
This section is for a language model that reads this repository.
grounded, missing_evidence or abstain.nmemory (nmemory --help). The MCP server is nmemory mcp serve (stdio). All 18 tool names start with nmemory_. Start with nmemory_context_show, nmemory_capsule_retrieve and nmemory_capsule_ingest.~/.nott/memory.toml. The variable NOTT_NMEMORY_CONFIG names another path. The store directory is ~/.nott/state/database/, or NOTT_DATABASE_DIR when a test sets it.| Page | Contents |
|---|---|
| Runbook | First useful result, failure diagnosis, backup and restore |
| Architecture | Trust boundaries and the full engine detail: store, recall, tools, CLI |
| Reference | Every CLI command and MCP tool, linked to its source |
| Rulebook | Implementation invariants |
| Setup | Development setup |
| Quality | Checks and security review |
| Docs index | Documentation index and a first contribution |
| Installation | Install paths |
| Privacy | Processing choices |
| Upgrade | Existing data |
| Troubleshooting | Failure diagnosis |
| Roadmap | Direction |
Run the checks from the repository root:
uv run ruff check . && uv run mypy --strict nmemory
TMPDIR=/var/tmp uv run --group dev pytest -q
Each test gets its own disposable store. No test touches your live store.
AGPL-3.0-only.