AWS Knowledge
Server Details
The AWS Knowledge MCP server is a fully managed remote Model Context Protocol server that provides real-time access to official AWS content in an LLM-compatible format. It offers structured access to AWS documentation, code samples, blog posts, What's New announcements, Well-Architected best practices, and regional availability information for AWS APIs and CloudFormation resources. Key capabilities include searching and reading documentation in markdown format, getting content recommendations, listing AWS regions, and checking regional availability for services and features.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.5/5 across 5 of 5 tools scored.
Each tool has a distinct purpose: regional availability, region listing, documentation fetching, skill retrieval, and searching. The descriptions clearly differentiate them, minimizing confusion.
All tools follow a consistent verb_noun pattern (e.g., list_regions, search_documentation) with a uniform aws___ prefix, making them predictable and easy to understand.
With 5 tools, the set is well-scoped for an AWS knowledge domain, covering essential operations without being too sparse or overly voluminous.
The tools cover search, region info, availability checks, documentation reading, and skill retrieval. Minor gaps exist (e.g., no direct service listing), but search can compensate, so the surface is largely complete.
Available Tools
5 toolsaws___get_regional_availabilityARead-onlyInspect
AWS resource availability per region.
Max 10 regions; multi-region needs
filters; single-region supportsnext_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.
| Name | Required | Description | Default |
|---|---|---|---|
| region | No | Unused; use `regions`. | |
| filters | No | Use exact AWS product or sub-feature name. - product: 'Amazon Bedrock' (service), or sub-features like 'Comprehend Auto Scaling', 'Latency-Based Routing', 'PrivateLink Support'. When the user names a specific sub-feature, filter on the sub-feature -- do NOT generalize to the parent service ('Amazon Comprehend'); that returns availability for the wrong scope. - api: 'SdkServiceId+Operation' (e.g. 'CloudFormation+CreateStack', 'IAM+GetSSHPublicKey') or 'SdkServiceId' (e.g. 'EC2'). Use a literal '+' between service and operation -- not space, colon, or hyphen. - cfn: 'AWS::EC2::Instance', 'AWS::Lambda::Function'. Include every region the user named; don't add filters they didn't request. Values must EXACTLY match AWS's catalog (e.g. 'AWS Lambda', not 'Lambda' or 'AWS Lambda Service'). If unsure of the exact name, first call once for one region with NO filters to list valid names, then filter on the exact match. | |
| regions | No | AWS region codes (max 10). Multi-region requires `filters`; single-region supports `next_token`. | |
| next_token | No | Pagination token. Single-region, no filters only. | |
| resource_type | Yes | Required: 'product' | 'api' | 'cfn'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it read-only and non-destructive. The description adds rich behavioral details: pagination with next_token constraints, multi-region requirements, exact filter matching with rejection behavior, and a recommended workflow to discover valid names. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with bullet points and front-loaded purpose, but slightly verbose. All sentences are valuable, no redundancy. Could be tightened but still effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but the description covers return status types, response keys, error behavior, and pagination. It doesn't detail the full response structure (e.g., whether it returns a list or object), but for a read-only tool with these constraints, it provides sufficient completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but description adds critical nuance: filter format (product, api, cfn sub-types), exact matching requirement, examples, and per-parameter constraints (max 10 regions, next_token only single-region). This goes well beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns AWS resource availability per region, with explicit distinction from sibling tools (search_documentation, list_regions) via the 'Not for' statement. The verb 'get' is implied in the name, and the description specifies the resource and scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (resource availability) and when not to (region counts, docs, vague queries), with direct references to alternatives. It also provides a fallback strategy for uncertain filter names, very helpful for correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
aws___list_regionsARead-onlyInspect
Retrieve a list of all AWS regions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false; the description adds no further behavioral details (e.g., pagination, rate limits) beyond confirming it is a read operation, meeting the baseline but not exceeding it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no extraneous information, achieving maximum conciseness for the tool's simple purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema, the description is adequate; however, it could be slightly improved by specifying the output format (e.g., region codes or names) to fully prepare the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the description's lack of parameter details is acceptable and meets the baseline expectation for a parameter-less tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve a list') and the resource ('all AWS regions'), effectively distinguishing it from sibling tools like 'aws___get_regional_availability' which focuses on availability within a region.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives; while the context implies it's for obtaining a full region list, there is no mention of when not to use it or how it compares to siblings like 'aws___search_documentation'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
aws___read_documentationARead-onlyInspect
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_lengthdefault 10000.start_indexdefault 0; use priorend_indexto 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/.
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}.
| Name | Required | Description | Default |
|---|---|---|---|
| requests | No | List of `{url, max_length?, start_index?}`. Batch 2-5. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false. Description adds significant behavioral context: use exact URLs, don't guess slugs, output includes truncated and redirected_url, error codes, and behavior of max_length/start_index. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: purpose first, then when-not-to-use, rationale, usage rules, parameter format, allow-listed prefixes, and output. Slightly long due to detailed allow-list, but every section serves a purpose and is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description thoroughly documents output fields (markdown, total_length, start_index, end_index, truncated, redirected_url) and error codes (not_found, invalid_url, throttled, downstream_error, validation_error). Covers all aspects needed for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value by specifying batch size of 2-5, explaining how start_index uses prior end_index or TOC offset, and clarifying max_length default. This goes beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Fetch full AWS doc pages as markdown,' clearly stating the verb and resource. It distinguishes from sibling 'search_documentation' by specifying that the search already returns chunks and this tool retrieves the full page.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (enumeration/aggregation needs complete set, no on-topic search results) and when not to use (don't reread a URL whose chunk you already have). Names the alternative tool 'search_documentation' and gives a rationale.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
aws___retrieve_skillARead-onlyInspect
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.
| Name | Required | Description | Default |
|---|---|---|---|
| file | No | Optional file path within the skill, copied as cited (e.g. `references/architecture.md`). Don't add or strip a `references/` prefix. Omit for SKILL.md. | |
| skill_name | Yes | Required. Exact `skill_name` from a search_documentation result, copied verbatim. Do not invent or modify. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and destructiveHint=false. Description adds behavioral context: requires exact skill_name from search, file must be copied as cited. Provides additional constraints beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: purpose, then two critical usage instructions. No filler, front-loaded with key information. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains return values (SKILL.md or file) and prerequisite search_documentation. Lacks error scenarios or handling of missing skills, but sufficient for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. Description adds nuance: 'copied as cited (e.g. references/architecture.md). Don't add or strip a references/ prefix.' For skill_name, it reinforces verbatim copying from search.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Retrieve' and resource 'AWS skill' with output defined: 'Returns SKILL.md, or `file` if given.' Explicitly distinguishes from sibling tools by requiring prior call to search_documentation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit prerequisite: 'Call search_documentation FIRST'. Warns against guessing or fabricating skill_name and file. Does not explicitly mention when not to use or alternatives, but the guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
aws___search_documentationARead-onlyInspect
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).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results per topic (default 5). | |
| topics | No | Up to 3 from: reference_documentation, current_awareness, troubleshooting, amplify_docs, cdk_docs, cdk_constructs, cloudformation, agent_skills, strands_docs, general. Default ["general"]. | |
| search_phrase | Yes | Keywords; preserve exact error strings and all task terms verbatim. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds that results contain verbatim page text and that answers should be derived directly from it, providing useful behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with bullet points and front-loaded with the main purpose. It is somewhat lengthy given the detail, but every sentence is informative and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fully explains the result format (rank_order, url, title, context). It covers parameter details, usage guidelines, and sibling differentiation, making it complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant value: for search_phrase, it instructs to preserve exact error strings verbatim; for topics, it lists and explains each valid option; for limit, it notes default 5.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's an 'AWS docs search' and explains that results contain verbatim page text. It distinguishes from sibling tools like read_documentation by specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidelines: 'Use read_documentation only when the chunks genuinely lack the needed detail' and instructions on topic selection ('Pick ONE topic. Add a 2nd ONLY if query genuinely spans domains').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
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