PT-Edge
Server Details
Live AI ecosystem intelligence — 47 tools for discovering, comparing, and tracking open-source AI projects, HuggingFace models and datasets, public APIs, and community discourse.
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
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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.
Tool Definition Quality
Average 4/5 across 8 of 8 tools scored. Lowest: 3.3/5.
Most tools have distinct purposes: describe_table, list_tables, and search_tables all help explore database structure but target different exploration needs (specific table details, overview, and keyword search respectively), while query, list_workflows, and get_status serve different query/analysis functions. However, find_ai_tool and search_tables could be confused as both involve searching, though find_ai_tool searches AI repos via semantic search while search_tables searches database metadata.
All tool names follow a consistent snake_case pattern with clear verb_noun structure: describe_table, find_ai_tool, get_status, list_tables, list_workflows, query, search_tables, submit_feedback. The naming is predictable and readable throughout the set.
With 8 tools, the count is well-scoped for a server focused on exploring an AI/ML database and finding AI tools. Each tool earns its place by covering distinct aspects: database exploration (describe_table, list_tables, search_tables), querying (query, list_workflows), AI tool discovery (find_ai_tool), and utility (get_status, submit_feedback).
The tool surface covers core workflows for database exploration and AI tool discovery effectively, with tools for orientation (get_status), structure exploration (list_tables, describe_table, search_tables), querying (query, list_workflows), and feedback (submit_feedback). A minor gap is the lack of a tool for updating or managing the database (e.g., write operations), but given the read-only focus and timeout/row limits in query, this is reasonable for the domain.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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