Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Local QMD search and bounded index maintenance through a Streamable HTTP MCP server.
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。
你需要
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"qmd": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/x1pher/qmd-mcp:v0.2.2"
]
}
}
}在终端中运行这条命令
claude mcp add qmd -- docker run -i --rm ghcr.io/x1pher/qmd-mcp:v0.2.2粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"qmd": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/x1pher/qmd-mcp:v0.2.2"
]
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"qmd": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/x1pher/qmd-mcp:v0.2.2"
]
}
}
}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 X1pheR 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(0.2.2)于36天前进入注册中心。
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 Docker。
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。
QMD MCP packages QMD as a long-running Streamable HTTP MCP server. It provides QMD search and document retrieval together with bounded index-maintenance operations, without exposing arbitrary shell execution.
This is a community-maintained integration. It is not affiliated with, endorsed by, or officially maintained by the upstream QMD project.
Use GitHub Issues for bug reports and feature requests and pull requests for proposed changes. See CONTRIBUTING.md for the development workflow, test requirements, and coding conventions. Security issues must follow the private process in SECURITY.md.
Release changes are recorded in CHANGELOG.md.
Release images are published on GitHub Container Registry (GHCR):
ghcr.io/x1pher/qmd-mcp:v0.2.2
Published packages are public, so Docker does not need a GitHub login to pull an accepted release.
For production deployments, select the stable version tag from an accepted GitHub Release. Retain its resolved digest as immutable provenance and rollback evidence.
The image supports linux/amd64 and linux/arm64. Each platform image retains only its matching QMD native llama runtime to keep the image bounded.
mkdir -p qmd/config qmd/content
cd qmd
Put the Markdown files you want QMD to index in content/.
config/index.ymlglobal_context: >-
This is a local Markdown knowledge base. Search results are discovery evidence; read the source document before relying on a material claim.
collections: docs: path: /vault pattern: "**/*.md" ignore:
notes: path: /vault/notes pattern: "**/*.md" includeByDefault: false
history: path: /vault/logs pattern: "history.md" includeByDefault: false embedding: false
path values refer to paths inside the container. The Compose example below mounts ./content at /vault.
embedding: false is a QMD MCP wrapper extension for collections that should remain lexical-only. The files are still indexed and available to explicit lexical (lex) searches, but they are excluded from embedding health and manual start_embed jobs. Use it for large append-only logs or other exact-lookup material where repeatedly rebuilding vectors adds cost without useful semantic recall.
compose.ymlservices:
qmd-mcp: image: ghcr.io/x1pher/qmd-mcp:v0.2.2 container_name: qmd-mcp environment: QMD_FORCE_CPU: "1" QMD_REFRESH_INTERVAL_MINUTES: "15" QMD_REFRESH_INITIAL_DELAY_SECONDS: "120" ports:
volumes: qmd-data:
The example binds the HTTP port to loopback only. If another container must call QMD MCP directly, attach both containers to a shared Docker network and use the QMD service name instead of exposing it broadly on the host.
QMD_FORCE_CPU=1 gives a predictable CPU-only deployment. Remove it or set it to 0 if you deliberately want QMD to probe for supported acceleration.
docker compose up -d
Check the service:
curl --fail http://127.0.0.1:8181/health
The Streamable HTTP MCP endpoint is:
http://127.0.0.1:8181/mcp
You can run the same release without Compose:
docker volume create qmd-data
docker run -d \ --name qmd-mcp \ --restart unless-stopped \ -p 127.0.0.1:8181:8181 \ -e QMD_FORCE_CPU=1 \ -e QMD_REFRESH_INTERVAL_MINUTES=15 \ -e QMD_REFRESH_INITIAL_DELAY_SECONDS=120 \ -v "$PWD/content:/vault:ro" \ -v "$PWD/config:/config:ro" \ -v qmd-data:/data \ ghcr.io/x1pher/qmd-mcp:v0.2.2
QMD MCP keeps QMD's read-oriented MCP tools and adds bounded administration operations:
health reports index and runtime state;start_update starts a bounded asynchronous filesystem reindex job;start_embed starts a bounded asynchronous embedding job;job_status reports recent administration jobs;start_embed, while embedding: false collections remain lexical-only;query runs with reranking disabled;query_reranked provides a separate CPU-heavy reranked path;source_relative_path for authoritative filesystem handoff when QMD_SOURCE_RELATIVE_ROOT is configured and the source path resolves unambiguously;exposeToUser=true and confirmUserApprovedExposure=true, and preview/show/open/render/inspect intent is not approval.Only one administration job runs at a time. Completed jobs are retained in memory with a bounded history. See docs/tools.md for the complete nine-tool reference, including access level and side effects.
The container uses these stable paths:
| Path | Purpose |
|---|---|
/config/index.yml | QMD collection configuration |
/data/index.sqlite | QMD index database |
/data/home | Runtime home directory |
/data/cache | Model and runtime cache |
Source collections should normally be mounted read-only. /data must remain writable because it contains the rebuildable index and model/runtime cache.
The Dockerfile provides working defaults for the normal runtime paths and HTTP listener. Override only the settings your deployment needs.
| Variable | Default | Purpose |
|---|---|---|
QMD_HTTP_HOST | 0.0.0.0 | HTTP listen address inside the container |
QMD_HTTP_PORT | 8181 | HTTP listen port |
QMD_CONFIG_PATH | /config/index.yml | QMD collection configuration file |
INDEX_PATH | /data/index.sqlite | QMD index database |
QMD_SOURCE_RELATIVE_ROOT | unset | Optional common source root. When set, query results include exact, collision-safe source_relative_path values relative to this root. |
QMD_DEFAULT_COLLECTION | unset | Default collection for start_embed; otherwise the first configured collection is used |
QMD_FORCE_CPU | 0 | Set to 1 to disable acceleration probing and force CPU use |
QMD_EMBED_PARALLELISM | unset | Optional QMD embedding parallelism override |
QMD_EMBED_MAX_DOCS_PER_BATCH | 8 | Default maximum documents per manual or scheduled embedding batch; accepted range 1-32 |
QMD_EMBED_MAX_BATCH_MB | 16 | Default maximum manual or scheduled embedding batch size in MiB; accepted range 1-128 |
QMD_EMBED_MAX_DURATION_MS | 3600000 | Maximum embedding session length; accepted range 60000-7200000 ms |
QMD_EMBED_INTERVAL_MINUTES | 0 | Automatic embedding check interval; 0 disables all embedding timers. Integer 0-1440 minutes |
QMD_EMBED_INITIAL_DELAY_SECONDS | 120 | First automatic embedding check delay; integer 0-3600 seconds |
QMD_REFRESH_INTERVAL_MINUTES | 15 | Scheduled index-refresh interval; refresh never starts embedding. 0 disables it, maximum 1440 |
QMD_REFRESH_INITIAL_DELAY_SECONDS | 120 | Delay before the first scheduled refresh; accepted range 0-3600 |
Invalid bounded numeric values fail at startup instead of being silently accepted. QMD_SOURCE_RELATIVE_ROOT never exposes its absolute path; only a relative source path is returned, and ambiguous normalized-path collisions return null rather than guessing.
Automatic embedding is disabled by default. Set a positive QMD_EMBED_INTERVAL_MINUTES to enable periodic checks after QMD_EMBED_INITIAL_DELAY_SECONDS.
Each check selects pending work using the effective collection embedding policy. Missing embedding means enabled; default search selection and QMD_DEFAULT_COLLECTION do not limit the scheduler. One scheduled_embed job processes eligible collections sequentially under the same maintenance claim as manual jobs and refresh. Across admitted checks, the first eligible collection rotates in process memory so one collection cannot consume every shared deadline indefinitely. Busy or active-query checks skip without queuing work. Policy and pending work are rechecked before each collection.
Scheduled embedding is resumable across cooperative deadlines. Successfully embedded chunks of an unfinished document are retained as internal checkpoints for the exact model/fingerprint, remain pending until the full document is complete, and are skipped on the next scheduled attempt. Incomplete checkpoint groups are excluded from vector-search results. Manual embedding keeps the previous atomic cleanup behavior for an interrupted incomplete document. Results preserve per-collection outcomes and current aggregate pending work. Cooperative deadline cancellation is reported as deadline debt rather than a model failure; genuine embedding failures keep their existing error handling. Successful/no-op/skipped checks are quiet; incomplete runs log a compact summary without document content.
MCP health and HTTP /health expose scheduledEmbedding enablement, interval, initial delay, last outcome, next planned check and reused embedding bounds. State is process-local and resets on restart. The next check is a plan, not a promised job start. scheduledRefresh.embeddingAutomatic: false describes refresh only: refresh remains update-only.
The scheduler uses one shared cooperative time budget. Its optional AbortSignal is forwarded through the pinned SDK, embedding session and native loops. After observing abort, no new document preparation, retry or native evaluation starts. Already-started native calls are awaited, including parallel workers. Completed scheduled chunks are checkpointed for later resume instead of being recomputed; an incomplete checkpoint group is not search-visible until all expected chunks exist. Shutdown clears scheduler timers and waits for actual maintenance completion before closing the store. A cooperative deadline cannot hard-limit an in-flight native call's wall-clock duration. Manual embedding retains its per-collection session duration and atomic incomplete-document cleanup; the absent duration default is 3600000 ms.
Use one server writer per index; other replicas or direct CLI writers are outside the process-local claim. Batch bytes are a packing target, not a RAM ceiling. Deployments must supply appropriate CPU/RAM/swap limits and embedding parallelism. Query deferral applies at admission and between collections; queries arriving during a collection keep the existing behavior.
node user.只显示了开头部分;其余内容请在仓库中阅读