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FoundryNet — Industrial Machine Intelligence

Server Details

Cross-OEM industrial machine intelligence: identity, normalization, automation, attestation.

Status
Unhealthy
Last Tested
Transport
Streamable HTTP
URL
Repository
FoundryNet/forge-mcp
GitHub Stars
0
Server Listing
foundry net-industrial

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

Full call logging

Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.

Tool access control

Enable or disable individual tools per connector, so you decide what your agents can and cannot do.

Managed credentials

Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.

Usage analytics

See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.

100% free. Your data is private.
Tool DescriptionsA

Average 4.5/5 across 30 of 30 tools scored. Lowest: 3.7/5.

Server CoherenceA
Disambiguation5/5

Every tool targets a distinct action or resource. Automation lifecycle tools are clearly differentiated (create, activate, delete, disable, restore, list). Prediction tools (predict, predict_batch, predict_breach, remaining_life) have unique purposes. Even the composite machine_intelligence tool is distinct as a single-call alternative. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., activate_automation, detect_anomalies, list_automations). The naming is predictable and intuitive, making it easy for an agent to infer functionality from the name alone.

Tool Count4/5

With 30 tools, the set is on the heavier side but well-justified for a comprehensive industrial machine intelligence platform covering identity, normalization, automation, predictions, health assessment, fleet management, and verification. Each tool earns its place without feeling bloated.

Completeness5/5

The tool surface is remarkably complete, covering the full lifecycle: machine identity (identify_machine), data normalization (normalize_telemetry, correct_mapping), automation (CRUD + lifecycle), predictions (single, fleet, breach, remaining life, accuracy), health (OEE, energy, health index, fleet health, anomaly detection, diagnosis), history queries, verification, and shift reports. No obvious gaps for the stated purpose.

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