Zendesk Live MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The three reporting tools (build_ticket_dashboard, dashboard_by_field, run_ticket_report) have overlapping purposes as they all produce ticket reports, though descriptions distinguish complete dashboards from single breakdowns and custom grouped reports. An agent could still confuse dashboard_by_field with run_ticket_report, but the guidance (e.g., 'use build_ticket_dashboard') helps.
Naming Consistency4/5
Five tools follow a clear verb_noun pattern (list, build, run, search, get), but dashboard_by_field breaks the pattern with a noun-phrase style, creating a minor inconsistency.
Tool Count5/5
Six tools is a reasonable number for a Zendesk reporting server, with no redundant or extraneous tools.
Completeness4/5
The tool set covers field discovery, ticket searching, detail retrieval, and multiple reporting/breakdown capabilities. The only notable gap is the lack of a direct 'list all tickets' tool, but search_live_tickets can fulfill this, so it's a minor gap.
Average 3.4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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
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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?
There are no annotations, so the description carries the full burden of behavioral disclosure. It mentions 'live' and 'recent date window' but does not disclose return format, pagination behavior, the meaning of 'live', or how the date window is applied. This leaves significant unknowns for a search 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 a single sentence with no wasted words and front-loads the verb 'Search'. However, it could benefit from a more structured presentation, such as mentioning key parameters or example usage.
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 the tool has 3 parameters, no annotations, no output schema, and several siblings, the description is under-specified. It does not explain the return format, the meaning of 'live', or how to construct the query, leaving the agent without enough context to reliably invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It references a query fragment (mapping to 'query') and a recent date window (likely 'months'), but the 'limit' parameter is completely undocumented. The phrase 'recent date window' is vague and does not clarify the parameter's behavior.
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 searches live Zendesk tickets using a Zendesk search query fragment and a recent date window. This distinguishes it from sibling tools like get_live_ticket_detail (which retrieves a single ticket detail) and report-generation tools.
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 about when to use this tool versus alternatives. The description implies a search use case but does not mention exclusions or when to prefer sibling tools like get_live_ticket_detail or run_ticket_report.
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 carries the burden, but it only says 'Create' without explaining if it's a read-only report or a mutating operation, nor does it disclose any limitations such as pagination or defaults. The word 'Create' could mislead an agent into thinking it's a state-changing operation.
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 short sentences, front-loaded with the action, and no filler. The distinction from build_ticket_dashboard is efficient and valuable.
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 has 4 parameters, no annotations, no output schema, and the description is minimal. It lacks parameter explanations, behavioral details, and return expectations. The mention of 'reconciled' and 'complete' raises questions rather than answering them.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about any parameters (field_name, limit, months, filters). The agent has to rely on names alone, which is insufficient.
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 states it creates a 'complete reconciled grouped breakdown', which is specific about the action and output. It also distinguishes from sibling build_ticket_dashboard by noting that tool is for several sections. However, 'reconciled' is not explained and could be ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'For several sections, use build_ticket_dashboard', providing a clear alternative and a condition for when not to use this tool. However, it doesn't mention other sibling tools like run_ticket_report or list_report_fields, so coverage is partial.
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?
With no annotations, the description carries the transparency burden. It discloses that the tool fetches and reconciles every matching ticket and produces breakdowns from one shared dataset, hinting at heavy or expensive work and the importance of a single call. However, it does not mention permissions, side effects, rate limits, or what the response contains.
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 two sentences with no fluff. The first sentence establishes purpose and preference; the second explains core behavior and a critical usage constraint. Every word earns its place.
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 is complex (multiple breakdowns, shared dataset, 4 params) but has no output schema and minimal annotations. The description leaves out return format, data volume implications, how filters/dimensions interact, and what 'breakdowns' concretely means. This is incomplete for an agent deciding whether and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25% (only 'dimensions' has a description). The tool description mentions 'matching ticket' and 'breakdowns,' which vaguely relates to filters and dimensions, but does not explain months, limit_per_section, or how they influence the result. This is insufficient compensation for the low schema coverage.
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 tool fetches and reconciles every matching ticket, then produces multiple breakdowns. It distinguishes itself as the 'preferred tool for complete management dashboards' and includes a unique instruction to call exactly once, which differentiates it from sibling tools. However, it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it is preferred for complete management dashboards and should be called exactly once per dashboard. This implies when to use it, but it does not mention when not to use it or explicitly point to alternatives like dashboard_by_field or run_ticket_report.
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 provided, the description carries full responsibility for behavioral disclosure. It indicates a read-only fetch via 'Fetch', but does not disclose potential limitations, authentication requirements, error behavior, or any other side effects. This is a significant gap for a tool with no annotation support.
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 a single, front-loaded sentence with no redundant information. It earns its place by stating the core action and the optional comment inclusion without 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?
No output schema exists, so the description should help the agent understand what the response contains. It only says 'ticket' without specifying fields or structure. It also lacks information on error handling and edge cases, making it incomplete for a tool with no annotations and no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does clarify that ticket_id identifies the specific ticket and that include_comments optionally includes comments, adding meaning beyond the bare parameter names. However, it does not explain types or defaults (already in schema) or any additional semantics, so it is only partially compensating.
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 specific action: fetch a single live Zendesk ticket, with an optional comments flag. The verb 'Fetch' and resource 'one live Zendesk ticket' are precise, and it distinguishes from sibling tools like search_live_tickets and report tools by focusing on a single ticket detail.
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 retrieving one specific ticket, but it does not explicitly state when to use this tool versus alternatives like search_live_tickets. There is no mention of exclusions or alternative tools, so the guidance is only implied by the tool's purpose.
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 provided, the description must disclose behavioral traits. However, it only mentions the report is 'reconciled' and not to call repeatedly. It does not state whether the operation is read-only, what side effects occur, or what happens if called repeatedly. The 'do not call repeatedly' note is more of a usage guideline than a behavioral disclosure.
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 two sentences, front-loaded with the core purpose and immediately followed by a clear usage exclusion. Every word earns its place—no filler or redundancy.
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 gives purpose and usage, but with 5 parameters, no output schema, and no annotations, it leaves critical gaps: what 'reconciled' means, what the output format is, what each parameter does, and any side effects. This is not complete enough for an agent to confidently invoke without further clarification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter meaning. It only references 'combined group-by fields,' which touches on group_by but leaves limit, months, filters, and include_examples unexplained. This is insufficient for a 5-parameter tool.
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's function: 'Run one complete reconciled report with combined group-by fields.' It also distinguishes from sibling build_ticket_dashboard by explicitly saying not to use this tool repeatedly for dashboards. The verb 'run' and resource 'report' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when not to use the tool: 'Do not call this repeatedly to build a multi-section dashboard; use build_ticket_dashboard.' This clearly routes to the appropriate alternative sibling.
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?
With no annotations, the description carries the burden of disclosing behavior. It reveals that results are metadata-cached (performance/consistency behavior) and compact by default (response format). This goes beyond a simple restatement and gives useful context, though it does not mention potential staleness or whether the operation is read-only, which is likely but not stated.
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 exceptionally concise at two sentences, with the main purpose front-loaded and no filler. Every word earns its place, and the additional behavioral note is tightly integrated.
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?
For a simple one-parameter list tool with no output schema, the description covers the essential aspects: what it lists, the cached nature, and the default compact format. It lacks information about pagination or response shape, but given the low complexity and the parameter's schema description, the description is largely sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the sole parameter 'include_details' with a clear description, so the baseline is 3. The tool description adds contextual value by noting 'compact by default,' which pairs with the parameter's purpose, but it does not add new semantic information beyond what the schema already explains.
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 'report field names', which precisely defines the tool's function. It is distinct from sibling tools like 'build_ticket_dashboard' and 'run_ticket_report', which focus on dashboards and reports rather than listing field metadata.
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 explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. The mention of 'metadata-cached and compact' implies a lightweight use case, but this is not directly stated as a recommendation.
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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