Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Search and read the StitchAPI docs: search_docs finds relevant sections, get_doc reads a page.
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 …”。
适用于网页版、桌面版和手机版 Claude:
https://stitchapi.dev/api/mcp打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"docs": {
"command": "npx",
"args": [
"-y",
"@stitchapi/docs-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add --transport http docs https://stitchapi.dev/api/mcpclaude mcp add docs -- npx -y @stitchapi/docs-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"docs": {
"url": "https://stitchapi.dev/api/mcp"
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"docs": {
"command": "npx",
"args": [
"-y",
"@stitchapi/docs-mcp"
]
}
}
}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": {
"docs": {
"type": "http",
"url": "https://stitchapi.dev/api/mcp"
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"docs": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@stitchapi/docs-mcp"
]
}
}
}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。
ChatGPT 只能连接互联网上的服务器:
https://stitchapi.dev/api/mcp菜单名称可能因套餐和版本不同而略有差异。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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
注册名称已通过域名 stitchapi.dev 验证(注册中心会核实域名所有权)
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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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。
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于–,最新版本(1.1.0)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。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
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。
API stitching: turn any API into a typed, resilient function . Declare an endpoint once — its types, auth, and resilience — and call it like a local function. No server, no codegen, no config files. The same definition answers to your code, the CLI, and an AI agent alike.
📚 stitchapi.dev — documentation, guides & live playground
Zero runtime dependencies · ~21 kB min+gzip — a typical import { stitch } tree-shakes to ~19 kB, and with no transitive tree there is nothing else to install or audit. The cache engine and the OTLP exporter load lazily, on first use, so they are not in those figures. The size is an enforced budget in CI , not an aspiration.
Verifiable supply chain — every package publishes from GitHub Actions over OIDC with a signed npm build-provenance attestation , so you can confirm which commit and which workflow produced the tarball you installed. Each release also ships an SBOM in both SPDX and CycloneDX, and the repo is scored publicly by OpenSSF Scorecard .
Watch more
[!NOTE]
StitchAPI is at `1.0.0-rc.9`. The core runtime is feature-complete, zero-dependency, covered by a green test gate, and already running in production in two projects. We're validating in the wild before stamping a stable
1.0.0— pin an exact version and expect only small, documented changes. Feedback is welcome.
.with()A stitch is StitchAPI's core primitive: it takes a single endpoint and hands back a callable. You declare the contract once — input, output, auth, resilience — and call it like a local function. The same definition your code calls, the CLI runs and an AI agent invokes — and every caller gets a capability, not a credential. A service with more than one endpoint is a seam — a group of stitches that share a base URL, auth, and one runtime (throttle budget, store, trace sink).
import { stitch } from 'stitchapi';
import { z } from 'zod';
const getUser = stitch({ path: 'https://api.example.com/users/{id}', output: z.object({ id: z.number(), name: z.string() }), pick: 'data', });
const user = await getUser({ params: { id: 1 } }); // typed · validated
Keep the fetch or axios you already have — it's the adapter underneath. A stitch sits _above_ the transport and turns an endpoint into a function rather than replacing the call.
In almost every project there's a src/api/ folder of thin functions that fire an HTTP request and pull the payload out of the response. Everything that actually makes an integration reliable — auth lifecycle, retries, rate limits, timeouts, response validation, drift detection, observability — gets re-implemented at every call site, and each wrapper rots independently. fetch hands back opaque bytes, and raw bytes aren't what application code (or an AI agent) needs; both want structured, validated, observable results.
A stitch folds all of that back into the call:
Around raw fetch, you hand-roll… | …a stitch declares it once |
|---|---|
| Opaque bytes you parse and hope are the right shape | Schema-validated, typed results — drift caught on every call |
| A throw on the first failure, then it's on you | Retries with backoff + jitter, honoring Retry-After |
| One coarse timeout, if you remember it | Layered total / per-attempt timeouts with real aborts |
| No rate control — you meet the 429s in production | Proactive throttle: rate + concurrency caps, shared per host |
| A raw byte stream you frame and paginate yourself | SSE framing, delta concatenation, auto-pagination |
| Zero visibility into what the call did | A typed event stream + opt-in traces: latency, retries, drift |
There are plenty of ways to get a typed API client — spec-based generators, hand-authored contract clients, workflow platforms, or a folder of hand-rolled fetch wrappers. StitchAPI sits in a spot none of them cover: it turns one endpoint at a time into a resilient, validated, observable function — no spec, no codegen, no config files, no server; only explicit composition.
undefined three layers downstream.| Alternative | Needs | You maintain | StitchAPI instead |
|---|---|---|---|
| Spec-based codegen (openapi-generator, Orval, Kubb, …) | a complete OpenAPI spec | a generated SDK, regenerated on every API change | one endpoint at a time, validated live at runtime |
| Typed runtime clients (Zodios, ts-rest, …) | a hand-authored contract | your own retry / auth / rate-limit code around it | resilience, auth lifecycle, and drift detection built into the primitive |
| Workflow platforms (Windmill, n8n, …) | a server to deploy | flows inside someone else's runtime | a zero-dependency library; composition is just code |
Hand-rolled fetch wrappers | nothing | bespoke auth, retries, limits — re-solved per project | the same concerns, declared once per stitch |
For the full competitive landscape and positioning, see the Overview.
Knowing what a tool refuses to be is how you trust what it is:
fetch/axios are the substrate underneath; a stitch sits above the transport.No server, no codegen, no config files, no implicit inheritance — only explicit composition.
stitch(url | config) returns a typed callable; a service with more than one endpoint is a `seam` that shares base, auth, throttle budget, store, and trace sink across its members.start → progress → drift → result → done); await is sugar that returns the final validated value.warn / info / verbose finding instead of a silent undefined.Retry-After, pro只显示了开头部分;其余内容请在仓库中阅读