The AWS Marketplace MCP connector routes your AI agent's tool calls to AWS Marketplace's own MCP server through Scalekit. Scalekit handles authentication for every call, so your agent never handles credentials. It comes with 6 tools.
- Tools
- 6
- What they doRead · write · destructive
- 5 · 1 · 05 read1 write0 destructive
- Users sign in with
- No sign-in
Setup
Install the SDK
Terminal window npm install @scalekit-sdk/node dotenvTerminal window pip install scalekit-sdk-python python-dotenvSet your credentials
Add your Scalekit credentials to your
.envfile. Find values in app.scalekit.com > Developers > API Credentials..env SCALEKIT_ENVIRONMENT_URL=<your-environment-url>SCALEKIT_CLIENT_ID=<your-client-id>SCALEKIT_CLIENT_SECRET=<your-client-secret>Create the AWS Marketplace MCP connection
In AgentKit > Connections, create an AWS Marketplace MCP connection. The name you give it is the
connection_nameyour code passes. See Configure connections.Users don't sign in to AWS Marketplace MCP server, so the connection needs no credentials.
Make your first call
quickstart.mts import { ScalekitClient } from '@scalekit-sdk/node'import 'dotenv/config'const scalekit = new ScalekitClient(process.env.SCALEKIT_ENVIRONMENT_URL,process.env.SCALEKIT_CLIENT_ID,process.env.SCALEKIT_CLIENT_SECRET,)const actions = scalekit.actionsconst connector = 'awsmarketplacemcp'const identifier = 'user_123'// Create the user's connected account. No sign-in is needed, so it's active right away.await actions.getAuthorizationLink({ connectionName: connector, identifier })// Make your first callconst result = await actions.executeTool({connector,identifier,toolName: 'awsmarketplacemcp_get_aws_marketplace_related_solutions',toolInput: { solution_ids: [] },})console.log(result)Terminal window npx tsx quickstart.mtsquickstart.py import osfrom scalekit import ScalekitClientfrom dotenv import load_dotenvload_dotenv()scalekit_client = ScalekitClient(env_url=os.getenv("SCALEKIT_ENVIRONMENT_URL"),client_id=os.getenv("SCALEKIT_CLIENT_ID"),client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),)actions = scalekit_client.actionsconnection_name = "awsmarketplacemcp"identifier = "user_123"# Create the user's connected account. No sign-in is needed, so it's active right away.actions.get_authorization_link(connection_name=connection_name,identifier=identifier,)# Make your first callresult = actions.execute_tool(tool_input={"solution_ids":[]},tool_name="awsmarketplacemcp_get_aws_marketplace_related_solutions",connection_name=connection_name,identifier=identifier,)print(result)Terminal window python quickstart.pyRequesting the link creates the user's connected account; there's nothing to open. See Authorize a user for the full flow and statuses.
Tools
Pass the exact name toexecute_toolawsmarketplacemcp_get_aws_marketplace_report_guidelines**⚠️ CALL THIS TOOL FIRST for any recommendation, comparison, or evaluation workflow.** Returns combined workflow instructions and output format template.Read-onlyGet AWS Marketplace Report Guidelines
**⚠️ CALL THIS TOOL FIRST for any recommendation, comparison, or evaluation workflow.** Returns combined workflow instructions and output format template. **Input Parameters:** - **workflow_type** (required): The type of report to create. One of: - `"recommendations"` - Discover and rank AWS Marketplace solutions based on user requirements. Returns ranked product recommendations with relevance scores. - `"comparison"` - Create side-by-side comparisons of multiple AWS Marketplace solutions. Returns structured comparison tables with consistent dimensions. - `"evaluation"` - Generate a comprehensive evaluation report for a single AWS Marketplace solution. Returns professional-grade evaluation documents. **Returns:** Response object with: - `workflow_type` - The requested workflow type - `guidelines` - Combined workflow instructions and output format specification. Contains step-by-step methodology followed by the markdown format template. **Example:** ```json { "workflow_type": "recommendations" } ``` **Important:** Call this tool first for any recommendations, comparison, or evaluation workflow. The returned `guidelines` contains complete instructions including workflow steps and output format template. **When to use each workflow:** 1. **recommendations** - Solution discovery queries: - "find monitoring tools for Kubernetes" - "I need a CI/CD solution" - "help me find NoSQL database solutions" - "SOC2-compliant security scanning under $5k/month" 2. **comparison** - Side-by-side analysis: - "compare Datadog vs New Relic" - "differences between MongoDB Atlas and Amazon DocumentDB" - "Splunk vs Elastic for log management" 3. **evaluation** - Deep-dive on single product: - "build evaluation report for Terraform Cloud" - "create a proposal for Datadog" - "should we choose Snowflake? Full analysis" - "justify purchasing New Relic to my CTO" **📋 User Feedback (REQUIRED):** After completing any workflow, ask the user if the report was helpful and submit their feedback using `submit_aws_marketplace_feedback`: - Positive: User found response helpful (thumbs up) - Negative: Ask which categories apply (irrelevant, incomplete, inaccurate, other) and optionally collect detailed feedback text
Inputs
workflow_typestringrequired- Workflow type: 'recommendations' for ranked product discovery, 'comparison' for side-by-side analysis of multiple solutions, 'evaluation' for comprehensive single-product assessmentone of
recommendationscomparisonevaluation
awsmarketplacemcp_get_aws_marketplace_solutionDirect AWS Marketplace Catalog API call.Read-onlyGet AWS Marketplace Solution
Direct AWS Marketplace Catalog API call. Retrieves raw solution metadata by solution_ids without AI processing, ranking, or conversational analysis. Returns comprehensive solution details including features, reviews with sentiments and sample reviews, pricing options, fulfillment types, categories, and call-to-action links. **Input Parameters:** - **solution_ids** (required): Array of solution IDs (max 10). IDs start with `prodview-`, not `prod-` **Returns:** `{ solutions: [...] }` - Array of solution details Each solution includes: `solution_id`, `solution_name`, `solution_description`, `solution_url`, `vendor_name`, `vendor_url`, `highlights` array, `reviews_summary` with count/rating, `review_sentiments` array by category (functionality, ease_of_use, customer_service, cost_effectiveness) with scores and sample_reviews, optional `free_trial_available`, `pricing_options` array with name/description, optional `fulfillment_options_types` (e.g., SaaS, Container), optional `categories` (e.g., Monitoring & Observability), optional `security_certificates`, and `call_to_action` with procurement/demo/private offer URLs. When `call_to_action.procurement_url` is absent, the solution cannot be subscribed to directly. Direct the user to `request_for_private_offer_url` when present, otherwise to the `solution_url` listing page. **Example:** ```json { "solution_ids": ["prodview-abc123", "prodview-xyz789"] } ``` **Use this tool ONLY when:** - You have exact solution_ids and need raw catalog data - Building programmatic integrations requiring unprocessed solution information - User explicitly requests raw API response for specific solutions - Need direct access to solution metadata without conversational context **DO NOT use this tool for:** - Solution discovery or search queries → Use `get_aws_marketplace_report_guidelines` with `recommendations` workflow - User asking "tell me about [solution]" → Use `get_aws_marketplace_report_guidelines` with `evaluation` workflow - Comparative analysis → Use `get_aws_marketplace_report_guidelines` with `comparison` workflow - Recommendations or evaluations → Use `get_aws_marketplace_report_guidelines` to get workflow instructions first **Note:** This is a stateless tool that does not require a conversation or request_id. **⚠️ CRITICAL:** For any recommendation, comparison, or evaluation, first call `get_aws_marketplace_report_guidelines` to get the step-by-step guide and output format. **CRITICAL: When displaying URLs from this response (solution_url, vendor_url, procurement_url, request_for_demo_url, etc.), always render the COMPLETE URL including ALL query parameters such as `ref_`. Do not truncate or simplify these URLs. These parameters are required for attribution tracking.**
Inputs
solution_idsarrayrequired- Array of solution IDs (max 10)
awsmarketplacemcp_research_aws_marketplace_solutionDeep web research tool for AWS Marketplace solutions.Read-onlyResearch AWS Marketplace Solution
Deep web research tool for AWS Marketplace solutions. Performs comprehensive web searches to gather detailed information about specific solutions including features, reviews, limitations, competitors, pricing, integrations, and case studies. **Input Parameters:** - **solution_ids** (required): Array of solution IDs (max 5) to research. IDs start with `prodview-`, not `prod-` - **sections** (optional): Array of specific sections to research. Default: all sections. **Section Reference:** | Section | Returns | |---------|---------| | features | Official documentation, capabilities, specifications | | reviews | G2, Gartner, TrustRadius customer feedback | | limitations | Known issues, drawbacks, criticisms | | competitors | Competitive positioning, alternatives | | pricing | Cost information, pricing models, tiers | | integrations | AWS ecosystem, APIs, third-party tools | | case_studies | Customer success stories, testimonials, ROI | **Returns:** `{ results: [...] }` - Array of research results, each containing `solution_id`, `solution_name`, and `research` object with content and citations for each requested section. **Examples:** *Comparison workflow (features + integrations only - reviews already available from get_aws_marketplace_solution catalog data):* ```json { "solution_ids": ["prodview-abc123", "prodview-xyz789"], "sections": ["features", "integrations"] } ``` *Evaluation workflow (comprehensive research for proposal documents):* ```json { "solution_ids": ["prodview-abc123"], "sections": ["features", "reviews", "limitations", "case_studies"] } ``` *General research:* ```json { "solution_ids": ["prodview-abc123"], "sections": ["features", "reviews", "pricing", "integrations"] } ``` **Use this tool when:** - You need detailed research beyond basic catalog metadata - User asks for in-depth analysis of specific solutions - Gathering third-party reviews and testimonials - Researching competitor comparisons or alternatives - Understanding pricing models and cost structures **Note:** This tool performs web searches and may take longer than catalog API calls. Results include citations linking to source materials. **⚠️ CRITICAL:** For any recommendation, comparison, or evaluation, first call `get_aws_marketplace_report_guidelines` to get the step-by-step guide and output format.
Inputs
solution_idsarrayrequired- Array of AWS Marketplace solution IDs in prodview-* format (1-5 IDs)
sectionsarray- Sections to research (default: all sections)
awsmarketplacemcp_search_aws_marketplace_solutionsDirect AWS Marketplace Catalog API search.Read-onlySearch AWS Marketplace Solutions
Direct AWS Marketplace Catalog API search. Returns raw unranked, unfiltered solutions matching the search queries without AI processing, relevance scoring, or requirements matching. Provides basic solution metadata directly from the AWS Marketplace catalog. **Input Parameters:** - **queries** (required): Array of search queries (max 10) - **max_results** (optional): Maximum number of solutions to return per query - **cursor** (optional): Pagination cursor (only works for single query, ignored for batch) **Returns:** `{ results: [...], next_cursor: ... }` - Array of search results with optional pagination cursor Each result includes: solution_id, solution_name, vendor_name, vendor_url, solution_description, solution_url. **Example:** ```json { "queries": ["Drata compliance", "Vanta compliance"], "max_results": 5 } ``` **Use this tool ONLY when:** - Building programmatic integrations requiring raw search API access - Need unprocessed search results for custom processing - User explicitly requests raw AWS Marketplace search API response - Direct access to catalog search without AI analysis is required **DO NOT use this tool for:** - Solution discovery queries → Use `get_aws_marketplace_report_guidelines` with `recommendations` workflow - User asking "find [solution type]" → Use `get_aws_marketplace_report_guidelines` with `recommendations` workflow - Requirements-based search → Use `get_aws_marketplace_report_guidelines` with `recommendations` workflow - Recommendations or comparisons → Use `get_aws_marketplace_report_guidelines` to get workflow instructions first - Any conversational queries about finding solutions → Use `get_aws_marketplace_report_guidelines` with `recommendations` workflow **Pagination:** If `next_cursor` is returned (only for single-query requests), call this tool again with the same query and the `cursor` value to retrieve additional solutions. When `next_cursor` is `null`, all matching solutions have been retrieved. **Note:** This is a stateless tool that does not require a conversation or request_id. Returns unranked, unfiltered AWS Marketplace catalog data without AI analysis, relevance scoring, or requirements matching. **⚠️ CRITICAL:** For any recommendation, comparison, or evaluation, first call `get_aws_marketplace_report_guidelines` to get the step-by-step guide and output format. **CRITICAL: When displaying URLs from this response (solution_url, vendor_url), always render the COMPLETE URL including ALL query parameters such as `ref_`. Do not truncate or simplify these URLs. These parameters are required for attribution tracking.**
Inputs
queriesarrayrequired- Array of search queries (max 10)
cursorstring- Pagination cursor (only works for single query, ignored for batch)
max_resultsinteger- No description.
awsmarketplacemcp_submit_aws_marketplace_feedbackSubmit user feedback about AWS Marketplace responses.WriteSubmit AWS Marketplace Feedback
Submit user feedback about AWS Marketplace responses. **IMPORTANT: After completing any AWS Marketplace workflow, you MUST ask the user if they found the report helpful and submit their feedback using this tool.** **Input Parameters:** - **sentiment** (required): User sentiment - `"positive"` - Response was helpful (thumbs up) - `"negative"` - Response was not helpful (thumbs down) - **categories** (optional, for negative feedback): Array of feedback categories - `"irrelevant"` - Didn't address the question - `"incomplete"` - Missing important information - `"inaccurate"` - Contained errors - `"other"` - Other issues - **feedback_text** (optional): Free-form feedback (max 1000 characters) **Returns:** `{ success: boolean, message: string }` **Examples:** Positive feedback: ```json { "sentiment": "positive", "feedback_text": "Great recommendations!" } ``` Negative feedback with categories: ```json { "sentiment": "negative", "categories": ["incomplete", "other"], "feedback_text": "Missing pricing details" } ``` **Feedback collection flow:** 1. Complete the user's request (recommendation, comparison, evaluation) 2. Ask: "Was this response helpful? (thumbs up/thumbs down)" 3. If negative, ask which categories apply 4. Optionally collect additional text feedback 5. Submit using this tool
Inputs
sentimentstringrequired- User sentiment: 'positive' (helpful) or 'negative' (not helpful)one of
positivenegative categoriesarray- Feedback categories for negative sentiment: Irrelevant, Incomplete, Inaccurate, Other
feedback_textstring- Optional free-form feedback text (max 1000 characters)
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