Microsoft Fabric — the complete, unedited output of the deterministic mcptrustchecker engine v1.13.0, scanned . Every finding, capability tag and score component below is exactly what the engine produced — no AI, no post-processing.
{
"tool": {
"name": "mcptrustchecker",
"version": "1.13.0",
"methodologyVersion": "mcptrustchecker-1.13"
},
"target": {
"id": "microsoft-fabric-mcp",
"source": {
"kind": "package",
"origin": "microsoft-fabric-mcp"
},
"server": {
"name": "microsoft-fabric-mcp"
}
},
"grade": "A",
"score": {
"score": 96,
"threatScore": 100,
"grade": "A",
"band": "A",
"categorySubtotals": {
"injection": 0,
"exfiltration": 0,
"permissions": 0,
"supply-chain": 0,
"network": 0,
"hygiene": 0
},
"vector": [
{
"kind": "client",
"term": "capability-exposure",
"level": "moderate",
"label": "capability blast radius (moderate) — client exposure if the model is manipulated",
"appliedPenalty": 3
},
{
"kind": "client",
"term": "verification-discount",
"level": "repo",
"label": "publisher verification (public source) — no provenance, but the source is public and inspectable",
"appliedPenalty": 1
},
{
"kind": "client",
"term": "coverage-honesty",
"level": "source",
"label": "inspection depth (source) — how much of the target the scan could see",
"appliedPenalty": 0
}
],
"gatesFired": [],
"methodologyVersion": "mcptrustchecker-1.13"
},
"capability": {
"level": "moderate",
"reasons": [
"reads sensitive or local data"
],
"tags": [
"sensitive-source"
]
},
"coverage": {
"level": "source",
"inputs": {
"toolSurface": true,
"implementationSource": true,
"packageMetadata": true,
"liveTransport": false
},
"caveats": [
"Tools were statically extracted from the published source (27 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command \"npx -y <package>\"."
]
},
"findings": [],
"toxicFlows": [],
"capabilities": [
{
"tool": "get_table_schema",
"tags": [],
"reasons": {}
},
{
"tool": "get_all_schemas",
"tags": [],
"reasons": {}
},
{
"tool": "list_workspaces",
"tags": [],
"reasons": {}
},
{
"tool": "list_lakehouses",
"tags": [],
"reasons": {}
},
{
"tool": "list_tables",
"tags": [],
"reasons": {}
},
{
"tool": "list_connections",
"tags": [],
"reasons": {}
},
{
"tool": "list_items",
"tags": [],
"reasons": {}
},
{
"tool": "get_item",
"tags": [],
"reasons": {}
},
{
"tool": "get_workspace",
"tags": [],
"reasons": {}
},
{
"tool": "list_capacities",
"tags": [],
"reasons": {}
},
{
"tool": "list_workspaces_with_identity",
"tags": [],
"reasons": {}
},
{
"tool": "get_workspace_identity",
"tags": [],
"reasons": {}
},
{
"tool": "list_shortcuts",
"tags": [],
"reasons": {}
},
{
"tool": "get_shortcut",
"tags": [],
"reasons": {}
},
{
"tool": "list_workspace_shortcuts",
"tags": [],
"reasons": {}
},
{
"tool": "list_job_instances",
"tags": [],
"reasons": {}
},
{
"tool": "get_job_instance",
"tags": [],
"reasons": {}
},
{
"tool": "list_item_schedules",
"tags": [],
"reasons": {}
},
{
"tool": "list_workspace_schedules",
"tags": [],
"reasons": {}
},
{
"tool": "list_environments",
"tags": [],
"reasons": {}
},
{
"tool": "get_environment_details",
"tags": [
"sensitive-source"
],
"reasons": {
"sensitive-source": [
"keyword \"get_env\""
]
}
},
{
"tool": "list_compute_usage",
"tags": [],
"reasons": {}
},
{
"tool": "get_item_lineage",
"tags": [],
"reasons": {}
},
{
"tool": "list_item_dependencies",
"tags": [],
"reasons": {}
},
{
"tool": "get_data_source_usage",
"tags": [],
"reasons": {}
},
{
"tool": "clear_fabric_data_cache",
"tags": [],
"reasons": {}
},
{
"tool": "clear_name_resolution_cache",
"tags": [],
"reasons": {}
}
],
"surfaceDigest": "0aadd570457b9c9c77266ae365afd5edaa23916b33acec6a1cdce123fb42230b",
"stats": {
"tools": 27,
"prompts": 0,
"resources": 0,
"findingsBySeverity": {
"critical": 0,
"high": 0,
"medium": 0,
"low": 0,
"info": 0
}
}
}