MCP Movidesk Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a clear, distinct resource and action: ticket creation, ticket retrieval, knowledge search, interaction addition, ticket listing by client, client lookup, status change, and agent assignment. There is no overlap or ambiguity between them.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in Portuguese, using snake_case throughout (e.g., criar_ticket, consultar_ticket, alterar_status_ticket). The naming is predictable and readable, with no mixed conventions.
Tool Count5/5
With 8 tools, the server provides a focused set that covers the core ticket management workflow without being bloated or too thin. Each tool serves a distinct function, making the count well-scoped for the domain.
Completeness4/5
The core ticket lifecycle is covered: create, retrieve, list by client, add interactions, change status, and assign. Minor gaps include lack of a general list-all-tickets endpoint and no update/delete for tickets, but these are workable for a support-focused toolset.
Average 4/5 across 8 of 8 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 is passing
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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 the full burden. It states it lists 'os últimos tickets' but does not disclose ordering semantics, whether filters are combined with AND/OR, whether at least one filter is required (all params are optional), or any side effects/permissions. This is a notable gap for a tool that could behave unpredictably without filters.
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. The first sentence states purpose and filters; the second gives a practical use case. No wasted words, and the key information is front-loaded.
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 no output schema and no annotations, the description should compensate with more detail about expected behavior, return format, and edge cases. The ambiguity about whether a filter is required and how the 'últimos tickets' are determined leaves the agent uncertain. It's adequate for a simple use case but not complete enough for reliable autonomous invocation.
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 100%, so each parameter already has a clear description. The tool description adds the overall context of filtering customer tickets but does not add meaning beyond the schema. Baseline 3 is appropriate.
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 uses a specific verb ('Lista') and resource ('tickets de um cliente específico'), and clearly specifies filter criteria (nome, email, documento). It distinguishes itself from siblings like criar_ticket (create) and consultar_ticket (single ticket lookup) by emphasizing listing history for a client.
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 explicitly states when to use: 'Útil para verificar histórico e evitar duplicidade antes de criar um novo ticket' (useful for checking history and avoiding duplicates before creating a new ticket). It provides clear context, though it does not explicitly mention alternatives or when not to use it.
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 provided, the description carries the full burden. It reveals that the tool returns all ticket information (status, responsible, client, interactions, custom fields, dates), which is useful. However, it does not explicitly state that the operation is read-only, nor does it mention possible error conditions (e.g., ticket not found) or rate limits, leaving some transparency gaps.
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 consists of two concise sentences. The first states the action and resource, the second lists the fields returned. Every word contributes value, and it is efficiently front-loaded with the core purpose.
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?
This is a simple tool with one parameter and no output schema. The description adequately explains the return value by listing key fields, which is sufficient for a lookup operation. Minor gaps remain, such as not describing behavior for non-existent tickets, but overall it is complete for the tool's complexity.
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 describes ticketId as 'ID numérico do ticket no Movidesk (ex: 12345)' with 100% coverage. The description only repeats 'ID numérico' without adding new meaning, such as how to obtain the ID or format constraints. The baseline score of 3 is appropriate since the schema does the heavy lifting.
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 'Busca' (fetches) and the resource 'ticket do Movidesk' by numeric ID, which distinguishes it from sibling tools like listar_tickets_cliente and alterar_status_ticket. It also enumerates the kind of data returned, making the tool's purpose unmistakable.
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: when you need complete details of a single ticket by ID. However, it does not explicitly provide when-to-use versus alternatives, such as when to prefer listar_tickets_cliente for multiple tickets. No exclusions or comparison to sibling tools are given.
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 to rely on, the description carries the burden of behavioral disclosure. It clearly indicates a search (non-mutating) operation and describes the source and workflow, but it does not disclose potential behavior such as what happens when no results are found, whether it is read-only, or any side effects. This is a moderate disclosure.
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 three sentences, front-loaded with the core purpose and then explaining the workflow. The third sentence about 'base de conhecimento viva' is somewhat redundant with the first two, but it adds a useful analogy without wasting 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?
Given the tool's complexity (3 parameters, 1 required, all documented in schema), the description adequately covers purpose, workflow, and return value (resolution instructions). It doesn't detail result structure, but with no output schema, this is not strictly required. Overall, it provides a solid, complete context for selecting and invoking the tool.
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 fully describes all three parameters, so the baseline is 3. The description only implicitly references the primary parameter (descricaoProblema) and does not add extra meaning about how incluirInteracoes or quantidadeResultados affect the search. Since schema coverage is 100%, the description doesn't need to compensate, but it also provides no additional value.
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 specifies a clear verb ('Pesquisa') and resource ('base de conhecimento do Movidesk (tickets resolvidos/fechados)'), clearly distinguishing this search tool from the sibling ticket-management tools. It states exactly what it does: receives a problem description, searches related tickets, and returns resolution instructions.
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 a clear workflow: 'Receba a descrição do problema, busque tickets relacionados e retorne instruções de resolução,' indicating when this tool should be used. It doesn't explicitly name alternatives or exclusions, but the context makes its intended use clear as a knowledge-base search rather than a ticket mutation.
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 disclose behavioral traits. It fails to state whether the tool returns a boolean existence flag, a list of matches, or full contact records, and does not explain behavior when multiple parameters are provided or none are given. The verb 'consulta' implies read-only, but the lack of return format info leaves a significant gap.
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 redundancy. The first sentence packs the core purpose and search method, and the second adds a direct usage directive. It is front-loaded and every sentence earns its place.
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?
With no output schema and no annotations, the description should outline return values and edge cases. It does not specify the output format or behavior for missing or multiple parameters. Although the tool is low complexity, these gaps make the description only partially complete for an agent.
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 descriptions cover all three parameters (100%), so the baseline is 3. The description only reiterates the search fields without adding new semantics such as exact vs. partial matching, AND/OR behavior, or the effect of omitting all parameters. It adds negligible value beyond the schema.
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 uses a specific verb ('Busca e consulta') and clearly identifies the resource ('base de contatos do sistema (Pessoas/Empresas)') and search criteria (Nome, Email, CPF/CNPJ). It distinguishes this tool from sibling tools focused on tickets and knowledge. The workflow hint 'antes de abrir tickets' further clarifies its unique role.
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 explicitly instructs 'Sempre use essa função se o usuário solicitar para checar um cliente, antes de abrir tickets.' This provides a clear conditional trigger and timing for use, which is sufficient for an agent to select this tool. Since no sibling tool offers the same lookup functionality, no alternatives are needed.
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 full burden and does disclose that some statuses require a mandatory justification. It does not, however, cover other behavioral aspects such as permission requirements, reversibility, or possible side effects like notifications, leaving some transparency gaps.
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 compact, front-loaded with the action, and uses two sentences to convey the core purpose and the conditional requirement. Every clause earns its place without redundancy.
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?
Given the simplicity of the tool and fully described parameters, the description covers the main purpose and the one non-obvious constraint (justification for certain statuses). It lacks explicit guidance on error scenarios or post-conditions, but for a status mutation tool this is adequate.
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 has 100% coverage with descriptions for all three parameters, so the baseline is 3. The description's mention of available statuses and justification requirement merely duplicates what is already in the property descriptions, adding no new semantic meaning.
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 'Altera' and the resource 'status de um ticket no Movidesk', which precisely distinguishes it from sibling tools that create, consult, or list tickets. It also lists the allowed statuses, reinforcing the specific action.
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 that this tool is for changing ticket statuses and enumerates the allowed statuses. However, it does not explicitly mention when not to use it or compare it with alternatives like adicionar_interacao or atribuir_agente, so it stops short of full exclusion 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 are provided, so the description carries the full burden. It discloses the core behavioral effect—'alterando o responsável (owner) do ticket'—which is valuable. However, it lacks details on permissions, reversibility, or side effects (e.g., notifications to the assigned agent), making it only moderately transparent.
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 action and purpose, with no redundant wording. It efficiently conveys the operation and its intended use.
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 straightforward assignment tool with no output schema, the description covers the action, the target resource, and the use case. It does not mention the response format or parameter interactions, but these are not critical for a simple mutation tool with well-described 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?
The schema covers all four parameters with descriptions (100% coverage), so the baseline is 3. The description does not add meaning beyond the schema; it only repeats the 'agente ou equipe' concept. The potential ambiguity between agenteId and equipe is not addressed, but that lies outside the description's added value.
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 assigns a ticket to a specific agent or team and changes the ticket's owner. This specific verb+resource combination distinguishes it from sibling tools like criar_ticket (create) or alterar_status_ticket (change status).
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 includes an explicit usage context: 'Use para escalonar ou redistribuir tickets entre a equipe.' This tells the agent when to apply the tool, but it does not explicitly mention alternatives or when not to use it, so it does not fully meet the highest bar.
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 are provided, so the description carries the burden. It discloses key behaviors: the ticket is created with a support macro formatted in HTML, supports macros 'atendimento' and 'escalonamento', and that client data MUST come from a real query. However, it does not mention side effects, error handling, or response formats, which are relevant 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: three sentences, front-loaded with the main action. Each sentence provides valuable information—purpose, use case, and a critical prerequisite—without superfluous detail.
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?
Given the tool's complexity (20 parameters, no output schema), the description is complete enough by covering the tool's purpose, usage context, macro types, and the mandatory prerequisite of using consultar_cliente. The schema handles parameter details, so the description does not need to enumerate all optional fields.
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?
Schema description coverage is 100% (0.0), so the baseline is 3. The description adds meaning beyond the schema by emphasizing that emailCliente must be obtained from 'consultar_cliente' and cannot be guessed, and by explaining the purpose of macro types ('atendimento' and 'escalonamento'). This raises the score.
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 'Cria um novo ticket no Movidesk' (Creates a new ticket in Movidesk) with a specific verb and resource. It also distinguishes from sibling tools by indicating that it creates tickets and supports macros, while sibling tools are for viewing, searching, or modifying tickets.
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: 'Ideal para registrar atendimentos após o suporte' (ideal for recording after support) and explicitly instructs to use 'consultar_cliente' BEFORE to retrieve client data, which is a strong usage guideline. It does not explicitly mention alternatives or exclusions, but the context is sufficient to know when to use it.
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 provided, the description carries the burden. It reveals that content is automatically formatted to HTML, which is a useful behavioral trait. However, it does not mention side effects, reversibility, or permission requirements, leaving some gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, followed by an important usage note. No wasted words; every sentence earns its place.
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 mutation tool, the description is complete: it defines the action, provides critical usage instructions, and notes formatting behavior. The schema covers all parameters, and no output schema is needed. It could mention return values or side effects, but these are not essential for this 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?
Schema coverage is 100%, so baseline is 3. The description adds value by instructing the agent to ask for the ticket number and how to source it via other tools, which directly informs the ticketId parameter. It also reiterates the HTML formatting, aligning with the conteudo description.
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 states a specific verb ('Adiciona') and resource ('interação em um ticket existente do Movidesk'), making the tool's purpose immediately clear. It distinguishes from siblings like 'criar_ticket' by specifying action on an existing ticket.
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?
It provides explicit instructions on when to use the tool: ask the user for the ticket number, and if the client name is given, first use 'consultar_cliente' and 'listar_tickets_cliente' to find the exact ticket ID. This gives clear context and alternatives.
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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