IoT Device Management MCP Server

by AiAgentKarl

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have clear distinct purposes, though device_analytics and get_fleet_dashboard both provide overviews and could cause slight confusion. However, descriptions help differentiate them.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern (e.g., register_device, get_alerts, send_command) with no mixing of conventions.
Tool Count5/5
9 tools cover the essential IoT device management operations well, including registration, listing, status, alerts, commands, and firmware updates. Not too few or too many.
Completeness2/5
Missing crucial device lifecycle operations: no update_device to modify attributes (e.g., location, name) and no delete_device to remove devices. These gaps can cause agent failures when managing device lifecycles.
Average 3.5/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose whether the tool is read-only, has side effects, or any required permissions. The behavioral transparency is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with the main purpose in the first sentence and parameters listed efficiently. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description lacks details on return format, available metrics, or any prerequisites. The tool is underspecified for an analytics function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description adds useful meaning: period_days is explained as analysis period in days, and device_id as optional filter for a specific device. This compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns analysis and statistics about the device fleet. Among sibling tools like get_alerts or get_device_status, this is distinct as an analytics-focused tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like get_fleet_dashboard. It only lists parameters without context on use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the behavioral burden. It states the tool marks an alert as resolved, but omits any side effects, permissions required, or whether the action is reversible. For a mutation tool, this is insufficient to inform an AI agent about potential impacts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no extraneous text, and the parameter table is efficiently structured. Every sentence earns its place, and the purpose is immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description covers the action and parameter semantics adequately for a simple mutation tool. However, it does not explain the return value, error conditions, or expected behavior (e.g., whether the alert is closed permanently). This is a minimal viable description but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully contextualizes both parameters. For alert_id, it specifies the source (aus get_alerts), and for resolution_note, it adds 'Optionale Notiz zur Loesung' (optional note for resolution), which goes beyond the schema's default value and naming.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Markiert' (marks) and the resource 'Alert', with the outcome 'als geloest' (as resolved). While it distinguishes from sibling tools like get_alerts by indicating a write action, it does not explicitly contrast with other mutation tools like register_device or send_command, but the purpose is sufficiently clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidelines are provided on when to use this tool versus alternatives, such as interacting with alerts via other functions. The description implies usage after get_alerts (via alert_id sourcing), but lacks explicit when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses filtering capabilities but does not explicitly state the tool is read-only or mention authentication, rate limits, or side effects. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with no fluff, using a short introductory sentence followed by clear bullet-like parameter explanations. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, yet the description fails to specify the return structure or type (e.g., a list of alert objects). This is a notable gap for an AI agent to understand the tool's output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter's purpose and defaults (device_id, severity with examples, resolved behavior, limit). This adds significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves alerts and warnings for IoT devices, specifying verb and resource. It does not explicitly differentiate from sibling tools like resolve_alert, but the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., resolve_alert for resolving, get_device_status for device-specific status). The description only describes the tool itself without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description describes a read operation (returning status/telemetry), but does not disclose potential side effects, authentication needs, error behavior, or whether it's safe. Minimal behavioral disclosure beyond stating what it returns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise lines in German, with a clear purpose and parameter explanation. No extraneous text; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is adequate: it states the function and parameter origin. However, it lacks details on the return format (e.g., is it JSON? what fields?), which an agent would need to parse the result. Vaguely says 'status and telemetry data'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, device_id, is explained in the description as coming from register_device or list_devices, adding context beyond the schema's title and type. This helps the agent know where to obtain valid IDs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the current status and telemetry data of a device, using a specific verb (returns) and resource (device status/telemetry). It distinguishes from siblings like get_alerts (returns alerts) and list_devices (lists devices).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The only contextual clue is the parameter description mentioning device IDs from register_device or list_devices, implying it's for already registered devices, but no when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It lacks details on pagination, rate limits, or what happens when no devices match the filters. The behavior of the tool is minimally described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence and a list of parameters. It is front-loaded with the main purpose and contains no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no required params, no output schema), the description covers the basic purpose and filtering meaning. However, it omits return format, pagination, and any side effects, making it adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meaning for all 4 parameters (device_type, location, status, tag) by stating they are filters and noting substring search for location. This provides helpful context beyond the schema's bare titles, though allowed values or examples are missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'registered IoT devices', and mentions optional filtering. It effectively distinguishes from sibling tools like get_device_status (single device) or register_device (creation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives. It does not mention exclusions, prerequisites, or contrast with siblings like get_fleet_dashboard or device_analytics.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. The description only states the registration action but omits important details like permissions required, side effects, or output behavior (e.g., confirmation or errors). This is inadequate for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with a clear one-line summary followed by an Args list. It is relatively concise, though the German text could be slightly tighter. No unnecessary sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool registers a device but the description lacks details on return values, error handling, or post-registration behavior. Without an output schema, the agent needs to know if it returns an ID or status. The description is incomplete for a 7-parameter, required-field tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides meaningful parameter explanations in the Args section, including examples (e.g., 'Temperatur-Sensor Halle A'). This adds value beyond the schema's property names and basic types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Registriert ein neues IoT-Geraet im System') with a specific verb and resource. The tool name 'register_device' matches its purpose, and siblings like 'list_devices' or 'send_command' are easily distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit when-to-use or when-not-to-use guidance. While the purpose is clear, there is no mention of alternatives or prerequisites, leaving the agent to infer based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the tool sends a command but does not mention side effects (e.g., device reboot), authorization requirements, rate limits, or idempotency. The minimal behavioral disclosure is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly concise at 5 lines, but it includes an 'Args' subsection that adds structure. It could be slightly more front-loaded by placing the core purpose in the first sentence, which it does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks output information; it does not describe what the tool returns (e.g., success/failure). Given no output schema and no annotations, the agent needs more context about the response format and error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the schema: device_id is defined as 'ID des Geraets', command includes examples like 'reboot', and parameters is described as optional JSON string. This compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool sends a remote command to an IoT device, with specific verb 'Sendet' and resource 'IoT-Geraet'. It lists example commands, differentiating it from sibling tools like list_devices or get_device_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for sending commands but provides no explicit guidance on when to use this tool versus alternatives or when not to use it. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose if the operation is read-only, data freshness, or side effects. It mentions no parameters but omits these details, potentially leading to misuse.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with main purpose and key feature (no params). No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the dashboard includes devices, alerts, and activities, but lacks details on output format or limits. Given no output schema and simple tool, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has zero parameters; the description adds value by explicitly stating no parameters are needed. Baseline 4 applies due to zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a complete fleet dashboard covering devices, alerts, and activities, requiring no parameters. This distinguishes it from sibling tools like list_devices or get_alerts, which are more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus siblings. It only notes that no parameters are needed, but fails to suggest scenarios, e.g., 'for a high-level overview' or 'instead of individual queries'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states that the tool 'simulates' a firmware update, which is a critical behavioral trait not captured by the input schema. This goes beyond the schema and compensates for the lack of annotations, though it does not detail permissions or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a one-sentence purpose and a clear list of parameter descriptions. No redundant information, though the German language might be slightly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the purpose and parameter meanings, but lacks information about the return value, success/failure behavior, and does not mention idempotency or side effects. Given no output schema, this gap reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description provides meaningful German explanations for each parameter, including examples for new_version and notes. This adds significant value over the schema's bare titles and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'simulates a firmware update for an IoT device', providing a specific verb (simulates) and resource (firmware update). This distinguishes it from siblings like send_command or get_device_status, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given on when to use this tool versus alternatives like send_command or device_analytics. The description implies it is for simulation, but it does not state that it should be used for testing or non-production environments.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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