mcp-server
Your company's brain for AI agents. Cited, permission-aware knowledge across every system.
Sollte ich dies verwenden
Qualität und Sicherheit
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"mcp-server": {
"url": "https://mcp.quelvio.com/http"
}
}
}Remote-Endpunkte
https://mcp.quelvio.com/httpstreamable-httpWas es kann
Tool-Inventar
Tools (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.
Eingabe-Schema
{
"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.
Eingabe-Schema
{
"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.
Eingabe-Schema
{
"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"
]
}Community
Nachweis