telecom-ai
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@telecom-aianalyze network traffic for anomalies"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Telecom Ai
MEOK AI Labs — telecom-ai MCP Server
MEOK AI Labs — telecom-ai MCP Server
🚀 Quick Start
# Install via pip
pip install telecom_ai
# Or install via Smithery
npx -y @smithery/cli@latest install telecom-ai --client claudeRelated MCP server: digital-human-library
✨ Features
MCP protocol compliant
Easy installation
Well-documented API
Production-ready
Active maintenance
📖 Documentation
🛡️ Compliance
This MCP server is built with EU AI Act compliance built-in:
✅ Article 9 — Risk Management System
✅ Article 13 — Transparency & Instructions for Use
✅ Article 15 — Bias Detection & Testing
✅ Article 26 — FRIA Support (where applicable)
✅ Article 50 — AI Content Watermarking (where applicable)
Need help getting compliant? Book a free 15-min diagnostic →
🏢 Enterprise
Need custom development, SLA guarantees, or white-label deployment?
Pro: $99/mo — Full MCP suite + EU AI Act tracking
Enterprise: $499/mo — Custom dev + SLA + Dedicated support
View Pricing → | Contact Sales →
🤝 Part of the MEOK Ecosystem
This server is part of the MEOK AI Labs ecosystem — 300+ MCP servers for sovereign AI governance.
Domain | Purpose |
EU AI Act compliance marketplace | |
AI safety & monitoring | |
Sovereign AI platform | |
Legacy modernization |
📜 License
MIT © CSOAI-ORG
Available Tools
1 tooltelecom_ai_complianceC
Assess regulatory compliance for AI in telecom networks and services. Covers net neutrality, lawful intercept, spectrum, and customer data.
| Name | Required | Description | Default |
|---|---|---|---|
| system_name | Yes | Name of the telecom AI system | |
| ai_function | Yes | Function (network optimization, predictive maintenance, customer churn, fraud, content filtering) | |
| data_types | Yes | Data processed (CDRs, location, browsing, traffic, metadata) | |
| network_impact | Yes | Impact on network (QoS, routing, throttling, prioritization) | |
| jurisdiction | Yes | Operating jurisdiction (EU, US/FCC, UK/Ofcom, etc.) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only lists areas covered but does not mention whether the tool is read-only, side effects, or any requirements like authentication. The description lacks important behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the core function. It is concise and directly states what the tool does without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about the output format (e.g., report, score, list). No output schema exists, and the description does not explain what the user can expect as a result. For a compliance tool, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptive parameter descriptions. The tool description adds no additional meaning beyond the schema. Baseline of 3 is appropriate as the schema already defines the parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool assesses regulatory compliance for AI in telecom, and lists four specific areas (net neutrality, lawful intercept, spectrum, customer data). This provides a specific verb+resource and distinguishes the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool or when not to use it. No alternatives or prerequisites are mentioned. The description simply states the function without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v1.0.0- First observed
telecom_ai_compliance
TDQS
With only a single tool, there is no risk of confusion. The tool's purpose is clearly defined, making it unambiguous for agent selection.
The tool name 'telecom_ai_compliance' follows a clear and predictable snake_case pattern, which is consistent. With one tool, naming is inherently uniform.
A single tool attempting to cover multiple complex regulatory areas (net neutrality, lawful intercept, spectrum, customer data) is too thin. The server's scope warrants multiple specialized tools, making the count inappropriate.
The tool touches on key compliance areas, but its broad scope suggests shallow coverage. Missing specific operations like detailed reporting or scenario analysis, leading to a borderline incomplete surface.
Maintenance
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