mcp-server
Your company's brain for AI agents. Cited, permission-aware knowledge across every system.
사용해야 할까요
품질 및 안전성
도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.
컨텍스트 비용
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": {
"mcp-server": {
"url": "https://mcp.quelvio.com/http"
}
}
}원격 엔드포인트
https://mcp.quelvio.com/httpstreamable-http할 수 있는 일
도구 목록
도구 (3)
🟢query_knowledge(query, mode, max_sources, domain)
Search the company's connected knowledge across every source — Drive, SharePoint, Confluence, Slack, Notion — with cited synthesized answers, lifecycle awareness, and refusal-on-weak-context. Returns a written answer with [n] citations plus the ranked source chunks. Modes: `fast` (1,500 kT — retrieval-only, no synthesis), `standard` (12,500 kT — default; synthesized answer over the top retrieval set), `deep` (25,000 kT — wider retrieval + premium synthesis for complex questions). Pick the cheapest tier that answers the question. Responses are capped at 25,000 output tokens per Claude Connectors policy; if truncated, structured metadata carries `truncated: true` and `query_id` so the agent can call `get_source_detail` for full provenance.
입력 스키마
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Natural-language query (1–2000 characters). Be specific — results are ranked by authority + relevance, not keyword overlap."
},
"mode": {
"type": "string",
"description": "fast | standard | deep. Defaults to `standard`. `fast` returns chunks only (no synthesized answer); `standard` and `deep` return a synthesized answer with [n] citations + the source chunks.",
"enum": [
"fast",
"standard",
"deep"
]
},
"max_sources": {
"type": "number",
"description": "Number of source chunks to return (1–20, default 5). The 25K token cap may force fewer results regardless of this value.",
"minimum": 1,
"maximum": 20
},
"domain": {
"type": "string",
"description": "Optional taxonomy domain filter (e.g. 'engineering.platform'). Use `list_domains` to discover valid values for the tenant."
}
},
"required": [
"query"
]
}🟢list_domains(coverage_filter)
List the taxonomy domains the company has indexed — with document counts, expert counts, and coverage levels — so an agent can decide whether to query before spending a Knowledge Token. Returns one row per domain with the canonical `taxonomy_domain` slug, document/chunk counts, expert count, coverage level (expert | partial | none), the single_expert risk flag, and the top contributor by authority. Use the slug as the `domain` filter on a follow-up `query_knowledge` call. Zero Knowledge Tokens consumed.
입력 스키마
{
"type": "object",
"properties": {
"coverage_filter": {
"type": "string",
"description": "Optional comma-separated subset of expert,partial,none. Default: all three. Unknown tokens 400."
}
},
"required": []
}🟢get_source_detail(query_id)
Return per-chunk source provenance for a previous query — document path, lifecycle state, embedding timestamp, contributor, last-updated — useful for verifying a citation or surfacing trust signals to a downstream system. Pass a `query_id` returned by an earlier `query_knowledge` call. Returns 404 if the query_id is unknown OR belongs to a different tenant (indistinguishable to prevent info-leak). Zero Knowledge Tokens consumed.
입력 스키마
{
"type": "object",
"properties": {
"query_id": {
"type": "string",
"description": "UUID returned in the structured-metadata block of a prior `query_knowledge` response. Tenant-scoped — cross-tenant 404."
}
},
"required": [
"query_id"
]
}커뮤니티
증거