此 MCP 可以做什么
Assesses website reliability and discoverability, recommends digital experience platforms, and estimates related project budgets.
工具
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['siteUrl', 'emailAddress'], 'properties': {'siteUrl': {'type': 'string', 'description': 'URL of site to analyze'}, 'emailAddress': {'type': 'string', 'description': 'Email of the user'}}}
输入模式
{'type': 'object', 'required': ['jobId'], 'properties': {'jobId': {'type': 'string', 'description': 'The job ID returned by `start_discoverability_assessment`. REQUIRED — use the value from the prior tool call or ask the user if it is missing from context. Only invoke when the user explicitly asks to check status.'}}}
输入模式
{'type': 'object', 'properties': {}}
输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'properties': {'data': {'type': ['object', 'null'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid'}, 'modeOptions': {'type': 'array', 'items': {'type': 'string'}}}}, 'tool': {'type': 'string'}, 'message': {'type': ['string', 'null']}, 'success': {'type': 'boolean'}, 'errorCode': {'type': ['string', 'null']}, 'workflowTools': {'type': 'array', 'items': {'type': 'string'}}, 'hubSpotHandoff': {'type': 'string'}, 'consentLanguage': {'type': 'string'}, 'humanFallbackUrl': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'properties': {}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['reportId'], 'properties': {'reportId': {'type': 'string', 'description': 'The run ID of the Discoverability Assessment to retrieve. Must be a valid GUID. If the user has not provided it, ask them first.'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['reportId'], 'properties': {'reportId': {'type': 'string', 'description': 'ID of report to check status'}}}
输入模式
{'type': 'object', 'properties': {}}
输入模式
{'type': 'object', 'properties': {'email': {'type': ['string', 'null'], 'default': None, 'description': 'The email address already collected from the user, if available'}, 'lastName': {'type': ['string', 'null'], 'default': None, 'description': 'Optional last name already collected from the user'}, 'firstName': {'type': ['string', 'null'], 'default': None, 'description': 'Optional first name already collected from the user'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'properties': {'data': {'type': ['object', 'null'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid'}, 'modeOptions': {'type': 'array', 'items': {'type': 'string'}}}}, 'tool': {'type': 'string'}, 'message': {'type': ['string', 'null']}, 'success': {'type': 'boolean'}, 'errorCode': {'type': ['string', 'null']}, 'workflowTools': {'type': 'array', 'items': {'type': 'string'}}, 'hubSpotHandoff': {'type': 'string'}, 'consentLanguage': {'type': 'string'}, 'humanFallbackUrl': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['dataSet', 'from'], 'properties': {'to': {'type': ['string', 'null'], 'format': 'date-time', 'default': None, 'description': 'Inclusive end (ISO-8601); omit for now UTC.'}, 'from': {'type': 'string', 'format': 'date-time', 'description': 'Inclusive start (ISO-8601).'}, 'sector': {'type': ['string', 'null'], 'default': None, 'description': 'GICS sector label; only for dataSet=all.'}, 'dataSet': {'type': 'string', 'description': 'Dataset: all | rscore | performance | security | accessibility | discoverability | seo (website SEO only — not LLM brand discoverability)'}, 'maxRows': {'type': ['integer', 'null'], 'default': None, 'description': 'Cap rows returned; default 500.'}, 'version': {'type': ['integer', 'null'], 'default': None, 'description': 'Exact Version filter.'}, 'hadErrors': {'type': ['boolean', 'null'], 'default': None, 'description': 'Filter by HadErrors.'}, 'sectorCode': {'type': ['string', 'null'], 'default': None, 'description': 'GICS sector code (GICS_Code); only for dataSet=all.'}, 'subIndustry': {'type': ['string', 'null'], 'default': None, 'description': 'GICS sub-industry label; only for dataSet=all.'}, 'versionSince': {'type': ['integer', 'null'], 'default': None, 'description': 'Minimum Version (>=).'}, 'industryGroup': {'type': ['string', 'null'], 'default': None, 'description': 'GICS industry group label; only for dataSet=all.'}, 'industryGroupCode': {'type': ['string', 'null'], 'default': None, 'description': 'GICS industry group code; only for dataSet=all.'}}}
输入模式
{'type': 'object', 'required': ['sessionId', 'email', 'fullName'], 'properties': {'email': {'type': 'string', 'description': 'The email address of the user'}, 'fullName': {'type': 'string', 'description': 'The full name of the user'}, 'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'required': ['sessionId', 'inferredAnswers'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}, 'inferredAnswers': {'type': 'array', 'items': {'type': 'object', 'properties': {'evidence': {'type': ['string', 'null']}, 'answerIds': {'type': 'array', 'items': {'type': 'string', 'format': 'uuid'}}, 'confidence': {'type': ['number', 'null']}, 'questionId': {'type': 'string', 'format': 'uuid'}}}, 'description': "Answers inferred from the user's natural-language response. Each item must include the questionnaire questionId, one or more selected answerIds, optional confidence from 0 to 1, and optional evidence text."}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['answer', 'sessionId'], 'properties': {'answer': {'type': 'string', 'description': 'The answer from the user'}, 'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId', 'email', 'firstName', 'lastName', 'company'], 'properties': {'email': {'type': 'string', 'description': 'The required email'}, 'company': {'type': ['string', 'null'], 'description': 'Optional company name'}, 'lastName': {'type': ['string', 'null'], 'description': 'Optional last name'}, 'firstName': {'type': ['string', 'null'], 'description': 'Optional first name'}, 'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId', 'inferredAnswers'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}, 'inferredAnswers': {'type': 'array', 'items': {'type': 'object', 'properties': {'evidence': {'type': ['string', 'null']}, 'answerIds': {'type': 'array', 'items': {'type': 'string', 'format': 'uuid'}}, 'confidence': {'type': ['number', 'null']}, 'questionId': {'type': 'string', 'format': 'uuid'}}}, 'description': "Answers inferred from the user's natural-language response. Each item must include the questionnaire questionId, one or more selected answerIds, optional confidence from 0 to 1, and optional evidence text."}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['answer', 'sessionId'], 'properties': {'answer': {'type': 'string', 'description': 'The answer from the user'}, 'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId', 'email', 'firstName', 'lastName', 'company'], 'properties': {'email': {'type': 'string', 'description': 'The required email'}, 'company': {'type': ['string', 'null'], 'description': 'Optional company name'}, 'lastName': {'type': ['string', 'null'], 'description': 'Optional last name'}, 'firstName': {'type': ['string', 'null'], 'description': 'Optional first name'}, 'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['sessionId', 'inferredAnswers'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}, 'inferredAnswers': {'type': 'array', 'items': {'type': 'object', 'properties': {'evidence': {'type': ['string', 'null']}, 'answerIds': {'type': 'array', 'items': {'type': 'string', 'format': 'uuid'}}, 'confidence': {'type': ['number', 'null']}, 'questionId': {'type': 'string', 'format': 'uuid'}}}, 'description': "Answers inferred from the user's natural-language response. Each item must include the questionnaire questionId, one or more selected answerIds, optional confidence from 0 to 1, and optional evidence text."}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['answer', 'sessionId'], 'properties': {'answer': {'type': 'string', 'description': 'The answer from the user'}, 'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['brandOrUrl'], 'properties': {'brandOrUrl': {'type': 'string', 'description': 'Brand name or website URL to analyze'}, 'contactName': {'type': ['string', 'null'], 'default': None, 'description': 'Optional full name of the contact person'}, 'contactEmail': {'type': ['string', 'null'], 'default': None, 'description': 'Contact email (required before job is queued)'}}}
输出模式
{'type': 'object', 'properties': {'data': {'type': ['object', 'null'], 'properties': {'jobId': {'type': ['string', 'null']}, 'message': {'type': ['string', 'null']}, 'success': {'type': 'boolean'}, 'brandOrUrl': {'type': ['string', 'null']}, 'contactName': {'type': ['string', 'null']}, 'contactEmail': {'type': ['string', 'null']}, 'needsContactInfo': {'type': 'boolean'}}}, 'tool': {'type': 'string'}, 'message': {'type': ['string', 'null']}, 'success': {'type': 'boolean'}, 'errorCode': {'type': ['string', 'null']}, 'workflowTools': {'type': 'array', 'items': {'type': 'string'}}, 'hubSpotHandoff': {'type': 'string'}, 'consentLanguage': {'type': 'string'}, 'humanFallbackUrl': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['siteUrl', 'emailAddress'], 'properties': {'siteUrl': {'type': 'string', 'description': 'URL of site to analyze'}, 'emailAddress': {'type': 'string', 'description': 'Email of the user to receive the report'}}}
输出模式
{'type': 'object', 'properties': {'data': {'type': ['object', 'null'], 'properties': {'siteUrl': {'type': 'string'}, 'reportId': {'type': 'string', 'format': 'uuid'}, 'emailAddress': {'type': 'string'}}}, 'tool': {'type': 'string'}, 'message': {'type': ['string', 'null']}, 'success': {'type': 'boolean'}, 'errorCode': {'type': ['string', 'null']}, 'workflowTools': {'type': 'array', 'items': {'type': 'string'}}, 'hubSpotHandoff': {'type': 'string'}, 'consentLanguage': {'type': 'string'}, 'humanFallbackUrl': {'type': 'string'}}}
输入模式
{'type': 'object', 'required': ['keyword'], 'properties': {'keyword': {'type': 'string', 'description': 'Keyword or keywords to search in oshyn.com blogs'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'required': ['brandOrUrl'], 'properties': {'brandOrUrl': {'type': 'string', 'description': "Brand name or website URL to analyze (e.g. 'Staples Canada' or 'https://www.staples.ca'). REQUIRED — ask the user if not provided."}, 'contactName': {'type': ['string', 'null'], 'default': None, 'description': "Full name of the contact person (e.g. 'Jane Doe'). Optional — ask the user if they want to provide it."}, 'contactEmail': {'type': ['string', 'null'], 'default': None, 'description': 'Contact email address for the assessment. REQUIRED by the API but optional at the tool level so you can invoke once with only brandOrUrl, ask the user, then call again.'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'required': ['sessionId'], 'properties': {'sessionId': {'type': 'string', 'format': 'uuid', 'description': 'The sessionId from the current chat context'}}}
输入模式
{'type': 'object', 'properties': {'email': {'type': ['string', 'null'], 'default': None, 'description': 'The email address of the user'}, 'message': {'type': ['string', 'null'], 'default': None, 'description': 'The message from the user describing how Oshyn can help'}, 'lastName': {'type': ['string', 'null'], 'default': None, 'description': 'Optional last name of the user'}, 'firstName': {'type': ['string', 'null'], 'default': None, 'description': 'The first name of the user'}}}
输出模式
{'type': 'object', 'required': ['result'], 'properties': {'result': {'type': 'string'}}}
近期工具变更
类似的 MCP 服务器
AdButler
Manages AdButler advertisers, campaigns, ad items, audiences, zones, creatives, catalogs, and advertising reports.
Meta Council
Provides governed workflows for consulting, outreach, sales deals, invoices, marketing campaigns, content approvals, accounting a…
synter-ads
Manages cross-platform advertising campaigns, audiences, tracking, creative, landing pages, campaign audits, technology intellige…
synter-ads
Manages cross-platform advertising campaigns, audiences, tracking, creative, landing pages, campaign audits, technology intellige…
Stratalize Intelligence
Provides vendor, market, SaaS, workforce, government contract, public company, regulatory, competitive, and AI-brand intelligence…
Neotic
Enables agents to create contextual in-app experiences, announcements, and triggers.
CorpusIQ
Connects authenticated users to business systems such as CRM, ecommerce, advertising, analytics, email marketing, SEO, calendars,…
Riley Craig x402 Agent Store
Provides paid blockchain data and transaction reads, AI brand-visibility research, and company or lead enrichment services.