AWS Knowledge MCP Server 是官方的吗?
是的。它由 AWS 构建和托管,并在 awslabs MCP 项目中有文档说明。
@AWS Knowledge MCP Server
基本信息
AWS Knowledge MCP Server 是 AWS 提供的全托管远程服务器。它为智能体提供最新的 AWS 文档、API 参考、服务和 CloudFormation 资源的区域可用性,以及 AWS 智能体技能。无需认证,但受速率限制。
https://knowledge-mcp.global.api.aws/claude mcp add aws-knowledge --transport http https://knowledge-mcp.global.api.aws/Fetch full AWS doc pages as markdown. `search_documentation` already returns verbatim page chunks, so don't re-read a URL whose chunk you already have to "confirm" or "round out" an answer -- the chunk is the real page text; treat it as authoritative. Reading the full page is justified ONLY when the chunks genuinely lack the content: - an enumeration or aggregation ("list all X", "how many X") needs the complete set and the chunks show only part of it; - no search result is on-topic after refining the query, and a known doc URL would have the answer. Otherwise, answer from the chunks. Use exact URLs from `search_documentation`; don't guess slugs. Input: `requests: [{url, max_length?, start_index?}]`. Batch 2-5. - `max_length` default 10000. - `start_index` default 0; use prior `end_index` to continue, TOC offset to jump. Allow-listed prefixes: docs.aws.amazon.com; aws.amazon.com (not /marketplace); repost.aws/knowledge-center; docs.amplify.aws; ui.docs.amplify.aws; github.com/{aws-cloudformation/aws-cloudformation-templates, aws-samples/{aws-cdk-examples, generative-ai-cdk-constructs-samples, serverless-patterns}, awsdocs/aws-cdk-guide, awslabs/aws-solutions-constructs, cdklabs/cdk-nag} (README on `main`); constructs.dev/packages/{@aws-cdk-containers, @aws-cdk, @cdk-cloudformation, aws-analytics-reference-architecture, aws-cdk-lib, cdk-amazon-chime-resources, cdk-aws-lambda-powertools-layer, cdk-ecr-deployment, cdk-lambda-powertools-python-layer, cdk-serverless-clamscan, cdk8s, cdk8s-plus-33}; strandsagents.com/latest/documentation/docs/; karpenter.sh/docs/; Amazon Braket: {amazon-braket-sdk-python, amazon-braket-schemas-python, amazon-braket-default-simulator-python, amazon-braket-pennylane-plugin-python, amazon-braket-algorithm-library, qiskit-braket-provider, autoqasm, qirtoqasm}.readthedocs.io and github.com/amazon-braket/* (blob/tree/raw). Output: SUCCESS -- markdown + `total_length, start_index, end_index, truncated, redirected_url?` (truncated includes TOC with char ranges). ERROR -- `error_code` in {not_found, invalid_url, throttled, downstream_error, validation_error}.
AWS docs search. Each result's `context` is verbatim page text -- a real chunk of the actual page, not a short snippet -- and usually already contains the answer, so answer directly from it. Use `read_documentation` only when the chunks genuinely lack the needed detail. Pick ONE topic. Add a 2nd ONLY if query genuinely spans domains. Extra topics dilute ranking. - reference_documentation -- API/SDK/CLI specs, config params - current_awareness -- new/released/announced - troubleshooting -- errors, "how to fix" (NOT for conceptual/feature questions) - amplify_docs -- Amplify (+ language) - cdk_docs -- CDK concepts/guides - cdk_constructs -- CDK code samples, L3 - cloudformation -- CFN/SAM templates - strands_docs -- Strands Agents SDK (its Skills/agents concepts go here, NOT agent_skills) - agent_skills -- this tool's guided skills (load via `retrieve_skill`) - general (default) -- architecture, best practices, tutorials, feature behavior Results: rank_order (lower=better), url, title, context (verbatim page chunk -- answer directly from it).
Retrieve a list of all AWS regions.
AWS resource availability per region. - Max 10 regions; multi-region needs `filters`; single-region supports `next_token`. - Status: isAvailableIn | isNotAvailableIn | isPlannedIn | Not Found. - Response key: products | service_apis | cfn_resources. Not for region counts/docs/vague queries -- use `search_documentation` / `list_regions`. Filter values must EXACTLY match AWS's catalog names; guessed, partial, or pluralized names are rejected ("values in filter parameter do not exist"). If unsure of the exact name, first call once for a single region with resource_type set and NO filters to list all valid names, then re-call filtering on the exact match.
Retrieve an AWS skill (workflows, references). Returns SKILL.md, or `file` if given. Call `search_documentation` FIRST and copy `skill_name` verbatim -- it is an opaque registry ID. Never guess or fabricate `skill_name` or `file`.
AWS Knowledge MCP Server 是 AWS 提供的全托管远程 MCP 服务器,为 AI 智能体提供最新的 AWS 文档、API 参考、区域可用性数据和 AWS 智能体技能。它无需认证,也不需要 AWS 账号。
AWS 将其作为开源 AWS MCP servers 项目(awslabs)的一部分发布,目前已正式发布(GA)。AWS 变化很快,模型的训练数据很快就会过时;这个服务器让助手可以搜索和阅读实时文档,检查某个服务、API 或 CloudFormation 资源是否在指定区域可用,并在回答或编写基础设施代码之前加载分步的 AWS 技能。
该端点使用 Streamable HTTP,无需凭据。使用受速率限制和 AWS Site Terms 约束。
https://knowledge-mcp.global.api.aws
claude mcp add --transport http aws-knowledge https://knowledge-mcp.global.api.aws
打开 Settings → Connectors → Add custom connector,命名为“AWS Knowledge”并粘贴 URL。没有登录步骤。
在 ~/.cursor/mcp.json 中:
{
"mcpServers": {
"aws-knowledge-mcp-server": {
"url": "https://knowledge-mcp.global.api.aws"
}
}
}
在 .vscode/mcp.json 中:
{
"servers": {
"aws-knowledge-mcp-server": {
"type": "http",
"url": "https://knowledge-mcp.global.api.aws"
}
}
}
AWS 文档给出了使用 fastmcp 的 stdio 转 HTTP 代理:
{
"mcpServers": {
"aws-knowledge-mcp-server": {
"command": "uvx",
"args": ["fastmcp", "run", "https://knowledge-mcp.global.api.aws"]
}
}
}
文档。 aws___search_documentation 按主题搜索 AWS 文档,例如 reference_documentation、current_awareness(新发布或已公布的功能)、troubleshooting、amplify_docs 和 CDK 内容。每个结果的上下文都是真实的页面文本。aws___read_documentation 以 Markdown 获取完整文档页面;其描述要求模型仅在搜索片段缺少所需细节(例如完整列表)时使用。
区域。 aws___list_regions 返回所有 AWS 区域。aws___get_regional_availability 报告产品、服务 API 或 CloudFormation 资源在最多 10 个区域中是可用、不可用还是计划中;筛选值必须与 AWS 目录名称完全一致。
技能。 aws___retrieve_skill 返回 AWS 技能的 SKILL.md 或其中某个文件。技能名称必须从搜索结果中复制,不能猜测。
是的。它由 AWS 构建和托管,并在 awslabs MCP 项目中有文档说明。
不需要。服务器无需认证,AWS 表示没有 AWS 账号也可以开始使用。
AWS 没有为该服务器列出价格。使用受速率限制和 AWS Site Terms 约束。
不能。它使用的是公开的 AWS 知识:文档、区域可用性和技能,无法访问你的账号。
支持。把 URL 添加为远程 HTTP 服务器即可。仅支持 stdio 的客户端可使用 fastmcp 代理。
搜索结果是来自 AWS 自有索引的原文页面片段,另外还提供区域和可用性的结构化工具,这是一般网页搜索所没有的。
AWS Knowledge MCP Server 的远程 MCP 服务器是一个托管的 Model Context Protocol 端点,地址是 https://knowledge-mcp.global.api.aws/,AI 助手无需在本地安装或运行任何东西即可连接。
把端点 https://knowledge-mcp.global.api.aws/ 添加到任意支持 MCP 的客户端,比如 Claude Code、Cursor 或 VS Code。本页的接入代码块可以一步配置好每个客户端。
此收录尚未确认 AWS Knowledge MCP Server 的认证要求。连接前请查阅提供方文档。
AWS Knowledge MCP Server 暴露的是 streamable-http 端点,这是远程 MCP 服务器普遍使用、主流客户端都支持的传输方式。
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