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Glama
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Server Details

Anomaly detection API powered by physics simulation. Scan any data for outliers.

Status
Unhealthy
Last Tested
Transport
Streamable HTTP
URL

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.

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Tool DescriptionsB

Average 3.8/5 across 19 of 19 tools scored. Lowest: 2.6/5.

Server CoherenceA
Disambiguation3/5

The tools have overlapping purposes that could cause confusion, such as waveguard_scan and waveguard_scan_timeseries both detecting anomalies but in different data types, and waveguard_price_manipulation and waveguard_volume_check both targeting crypto manipulation detection. However, descriptions help clarify distinctions, like structural vs. time-series anomalies, preventing complete misselection.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with a 'waveguard_' prefix and descriptive nouns or noun phrases (e.g., waveguard_action_surface, waveguard_market_data). This uniformity makes the set predictable and easy to parse, with no deviations in style or convention.

Tool Count4/5

With 19 tools, the count is slightly high but reasonable for the broad domain of data analysis and anomaly detection in crypto and structured data. Most tools serve distinct functions, though some overlap suggests minor bloat, but it doesn't feel excessive for the server's scope.

Completeness4/5

The toolset covers a wide range of data analysis tasks, including anomaly detection, similarity comparison, risk assessment, and market data fetching, with clear workflows. Minor gaps exist, such as lacking direct data manipulation or export tools, but agents can work around these using the provided tools effectively.

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