PyStreamMCP/pystreammcp.toml at main · Mullassery/PyStreamMCP · GitHub

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[mcp]
enabled = true
port = 8772
discovery_method = "stdio"

[mcp.tools]
discover_mcp_projects = true
plan_query_execution = true
optimize_cross_project_query = true
execute_federated_query = true
detect_compatible_projects = true
rank_tools_by_relevance = true
handle_cross_database_join = true
cache_management = true
error_recovery_retry = true
report_performance_metrics = true
estimate_query_cost_multi_project = true
manage_endpoint_federation = true

[mcp.security]
require_auth = false
allowed_models = []

[mcp.performance]
cache_results = true
cache_ttl_seconds = 3600

[federation]
endpoints = [
    "http://localhost:8765/mcp",  # StatGuardian
    "http://localhost:8766/mcp",  # PyReverseETL
    "http://localhost:8767/mcp",  # PrismNote
    "http://localhost:8768/mcp",  # ClusterAudienceKit
    "http://localhost:8769/mcp",  # PyWeatherEnriched
    "http://localhost:8770/mcp",  # PyTerrainMap
    "http://localhost:8771/mcp",  # PyRoboFrames
]

[optimization]
enable_caching = true
enable_query_optimization = true
enable_cost_estimation = true
token_reduction_target_percent = 70