agent-signal
Server Details
Collective intelligence for AI shopping agents — product intel, deals, and more
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- dan24ou-cpu/agent-signal
- GitHub Stars
- 0
- Server Listing
- agent-signal
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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 30 of 30 tools scored. Lowest: 3.1/5.
The tools cover distinct aspects of shopping intelligence, but there is significant overlap in purpose. For example, 'smart_shopping_session', 'get_category_recommendations', and 'get_constraint_match' all aim to provide product recommendations, which could confuse an agent about which to use. Descriptions help clarify, but the boundaries between tools like 'detect_deal' and 'get_todays_deals' are not entirely clear, leading to potential misselection.
Most tools follow a consistent verb_noun pattern (e.g., 'add_to_wishlist', 'check_price_alerts', 'get_product_intelligence'), with clear and descriptive names. However, there are minor deviations like 'smart_shopping_session' (adjective_noun_noun) and 'agent_signal_status' (noun_noun_noun), which slightly break the pattern but do not severely impact readability.
With 30 tools, the set feels overly large and heavy for the shopping intelligence domain. Many tools have overlapping functionalities (e.g., multiple recommendation and analysis tools), suggesting redundancy. A more streamlined set of 10-15 tools could cover the same scope without overwhelming an agent, making the current count excessive.
The tool surface is highly complete for the shopping intelligence domain, covering the full lifecycle from session initiation ('smart_shopping_session') to outcome logging ('log_outcome'), with comprehensive analysis, recommendation, and monitoring tools. There are no obvious gaps; tools like 'import_completed_session' even allow retroactive data contribution, ensuring robust coverage.
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{
"$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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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
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Credentials required to access the server are missing or invalid
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