An MCP server that scores AI initiatives using four deterministic pillars: strategic alignment, financial return, change enablement, and governance risk. It returns an Accelerate/Fix/Stop classification, modelled EUR value ranges, decision confidence, benchmark lookups, taxonomy values, portfolio validation, and drag-cost calculations.
From the registry: AI Value Trace and BVF, the agentic-native conversation framework. Run a Trace on a named account.
$ npm install -g aibvf-mcphttps://www.npmjs.com/package/aibvf-mcp'}],Please install the `aibvf-mcp` MCP server into my current AI client (that's you).
Optional prerequisites:
- Install the aibvf-mcp package globally — Install the MCP server from npm so the `aibvf-mcp` command is available on your system. Run: `npm install -g aibvf-mcp` (https://www.npmjs.com/package/aibvf-mcp'}],)
Canonical MCP server config (stdio transport):
- command: `aibvf-mcp`
- args: []
- optional environment variables:
- `AIBVF_TELEMETRY_DISABLE`: Set to disable anonymous telemetry reporting. (example: `1`)
- `AIBVF_TELEMETRY_URL`: Optional custom telemetry backend URL. (example: `<your-telemetry-url>`)
- `AIBVF_TELEMETRY_KEY`: Optional key for the custom telemetry backend. (example: `<your-telemetry-key>`)
Note: README states the server uses stdio transport. No required environment variables are documented for normal operation.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.AIBVF_TELEMETRY_DISABLEDisables anonymous usage telemetry for the MCP server.AIBVF_TELEMETRY_URLSets a custom backend URL for telemetry.AIBVF_TELEMETRY_KEYSets the backend key used when sending telemetry to a custom backend.AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
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