Parsley - Buyer Intent Signals
Query buyer intent signals, MEDDIC qualifications, and lead scores from Parsley.
사용해야 할까요
품질 및 안전성
A
도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.
컨텍스트 비용
~1,122토큰 (도구 정의)
~1.1 KB일반적인 응답 크기
중간 정도의 주의 영향 (128k 컨텍스트의 0.88%)
이는 서버의 도구가 모델의 컨텍스트에 로드될 때마다 소비되는 대략적인 토큰 수입니다. 수치가 높을수록 다른 작업에 사용할 수 있는 주의가 줄어듭니다.
설치
원클릭 설치
`claude_desktop_config.json` 파일에 다음을 추가하세요:
{
"mcpServers": {
"parsley-mcp": {
"command": "npx",
"args": [
"@tryparsley/mcp-server"
]
}
}
}실행 가능한 패키지
npm@tryparsley/mcp-server
0.1.2stdio원격 엔드포인트
https://www.parsley.id/api/mcpstreamable-http할 수 있는 일
도구 목록
도구 (8)
🟢 읽기 전용🟡 쓰기🔴 삭제⚪ 알 수 없음
🟢get_conversations(days, lead_quality, intent_signal, limit, client)
List recent chatbot conversations with filtering by lead quality, intent signal, and date range.
입력 스키마
{
"type": "object",
"properties": {
"days": {
"default": 30,
"type": "number",
"minimum": 1,
"maximum": 365
},
"lead_quality": {
"type": "string",
"enum": [
"hot",
"warm",
"cold"
]
},
"intent_signal": {
"type": "string",
"enum": [
"high_intent",
"evaluation",
"research",
"support"
]
},
"limit": {
"default": 20,
"type": "number",
"minimum": 1,
"maximum": 50
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_conversation_detail(conversation_id, client)
Get full details of a single conversation: MEDDIC signals, engagement metrics, enrichment data, and any owner-configured discovery field values captured during the chat (e.g. company size, current tooling, hiring status).
입력 스키마
{
"type": "object",
"properties": {
"conversation_id": {
"type": "string"
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"required": [
"conversation_id"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_hot_leads(days, include_warm, client)
Get all hot and warm leads with MEDDIC evidence. The morning briefing tool.
입력 스키마
{
"type": "object",
"properties": {
"days": {
"default": 7,
"type": "number",
"minimum": 1,
"maximum": 365
},
"include_warm": {
"default": true,
"type": "boolean"
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_analytics_summary(days, client)
Dashboard-level overview: views, conversations, lead counts, conversion rate.
입력 스키마
{
"type": "object",
"properties": {
"days": {
"default": 30,
"type": "number",
"minimum": 1,
"maximum": 365
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢search_by_intent(meddic_signals, min_intent_score, topic, days, client)
Find conversations matching specific MEDDIC signals, intent score, or topic.
입력 스키마
{
"type": "object",
"properties": {
"meddic_signals": {
"type": "array",
"items": {
"type": "string",
"enum": [
"metrics",
"economic_buyer",
"decision_criteria",
"decision_process",
"identify_pain",
"champion"
]
}
},
"min_intent_score": {
"type": "number",
"minimum": 1,
"maximum": 5
},
"topic": {
"type": "string"
},
"days": {
"default": 30,
"type": "number",
"minimum": 1,
"maximum": 365
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_knowledge_gaps(days, topic, limit, client)
Surface unanswered questions from chatbot conversations, grouped by topic.
입력 스키마
{
"type": "object",
"properties": {
"days": {
"default": 30,
"type": "number",
"minimum": 1,
"maximum": 365
},
"topic": {
"type": "string"
},
"limit": {
"default": 20,
"type": "number",
"minimum": 1,
"maximum": 50
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_lead_enrichment(days, has_company, client)
Get extracted company, role, timeline, and budget context from conversations.
입력 스키마
{
"type": "object",
"properties": {
"days": {
"default": 30,
"type": "number",
"minimum": 1,
"maximum": 365
},
"has_company": {
"default": false,
"type": "boolean"
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_meddic_summary(days, client)
Aggregate MEDDIC signal distribution across all conversations.
입력 스키마
{
"type": "object",
"properties": {
"days": {
"default": 30,
"type": "number",
"minimum": 1,
"maximum": 365
},
"client": {
"description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}커뮤니티
증거
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