mcp-juridico-brasil

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct function: listing monitored processes, searching by number, listing courts, listing movements, generating structured summaries, monitoring updates, calculating deadlines, listing summons, and confirming reading. There is no overlap or ambiguity between these operations.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., listar_processos_monitorados, calcular_proximo_prazo). The naming is predictable and in Portuguese, matching the domain.
Tool Count5/5
With 9 tools, the server is well-scoped for managing Brazilian legal processes. Each tool serves a clear purpose without redundancy, covering search, listing, monitoring, and actions related to summons.
Completeness4/5
The tool set covers core workflows: searching by number, listing courts and movements, monitoring updates, calculating deadlines, and managing summons. Minor gaps exist, such as a general process search or bulk listing, but these are not critical for the intended legal assistant use case.
Average 4/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 12 commits in the last 12 weeks
- Last stable release on June 22, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 does not disclose behavioral traits such as read-only nature, required permissions, rate limits, or potential side effects. The description only states what it returns, not how it behaves or constraints.
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 primary action, and contains no extraneous information. Every sentence adds value without redundancy.
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 has an output schema and 3 parameters, the description covers the return fields but omits details on error handling, pagination, or performance implications. It is adequate but not thorough.
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 baseline is 3. The description does not add meaning beyond the schema for the parameters; it mentions the output format but no additional parameter nuance. Hence, neutral contribution.
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 lists recent movements of a judicial process, specifying it returns history with TPU code, name, date/time, ordered from newest to oldest. It distinctly differentiates from siblings like 'listar_processos_monitorados' which lists monitored processes.
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 when to use (when needing recent movements of a process) but provides no explicit guidance on when not to use or alternatives. Given sibling tools like 'resumir_andamento' exist, the lack of comparative context is a missed opportunity.
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 discloses that the tool uses polling (not real-time) and mentions future push notification, but does not detail side effects, authorization needs, or rate limits. Basic behavioral context is given but not comprehensive.
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: one sentence for purpose and two for implementation status. It is front-loaded with the core function. The technical details (DataJud, phases) are useful but could be considered slightly verbose for an agent; however, overall it is efficient.
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 3 parameters with full schema coverage and an existing output schema, the description is fairly complete. It explains the check and the data reference point. It does not mention prerequisites (e.g., whether the process must be pre-registered) but sibling tools suggest coverage. Slight gap in overall context.
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?
Input schema has 100% coverage; each parameter already has a description. The tool description adds no additional meaning beyond referencing 'data informada' which maps to 'desde_iso'. Baseline of 3 is appropriate as the description provides no extra value over 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 clearly states the tool's purpose: check if a process has an update after a given date. The verb 'verifica' and resource 'processo' are specific, and it distinguishes from sibling tools like 'buscar_processo_por_numero' or 'listar_processos_monitorados' by focusing on update checking.
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 via implementation phases (polling, not real-time) but does not explicitly state when to use this tool versus siblings like 'buscar_processo_por_numero' or 'listar_movimentacoes'. No direct comparison or alternatives are provided, so guidance is only implicit.
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 must convey behavior. It states it fetches from DataJud and returns formatted data with instructions, but lacks details on side effects, authentication, rate limits, or error handling.
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?
Three sentences, front-loaded with purpose, no redundant information. Slightly verbose second sentence could be tightened but overall efficient.
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 has two parameters (one required) and an output schema, the description adequately covers the purpose and behavior. It could mention that the return includes instructions, but that's implied.
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 coverage is 100% with descriptions for both parameters. The description adds no additional meaning beyond what the schema already provides, so baseline score of 3 applies.
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 structured data for LLM summarization, distinguishing it from sibling tools like buscar_processo_por_numero which likely fetch raw data. It explicitly notes that semantic processing remains with the model, not the MCP.
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 generating summaries but does not explicitly state when to use or avoid this tool versus alternatives. No direct comparison or exclusion criteria are provided.
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?
No annotations provided, so description carries full burden. It discloses read-only nature, secret justice suppression, and required credentials. However, it lacks details on rate limits, error behavior, or pagination beyond the limite parameter.
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 reasonably concise, front-loading purpose and read-only warning. Every sentence adds value, though the credential list could be slightly shorter if integrated.
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?
Output schema exists, so return values need not be detailed. The description covers read-only nature, secret justice, and credentials, but misses pagination behavior, ordering, or what recent means for default limite.
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 coverage is 100% with good parameter descriptions. The overall description adds minimal additional semantics for parameters beyond the schema, but the credential environment variables are helpful context.
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 lists communications from DJe (intimações, citações, notificações) and specifies it is read-only. It distinguishes itself from siblings like confirmar_leitura_intimacao by explicit read-only nature, though not referencing siblings directly.
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 says it is a read-only operation but does not explicitly guide when to use this tool versus alternatives like confirmar_leitura_intimacao or listar_processos_monitorados. Usage context is implied but not contrasted.
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 full behavioral disclosure. It describes the API source, coverage, and behavior with/without tribunal. However, it does not mention error handling (e.g., if number not found), rate limits, or authentication, leaving gaps.
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, at three short lines, and front-loaded with the core purpose. It includes necessary details without wordiness. Slight improvement could be structuring with bullet points, but it's effective.
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 (searching across many courts, returning various data fields), the description covers the main aspects: purpose, data source, coverage, and an important usage nuance (tribunal omission). An output schema exists, so return values need not be detailed.
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 coverage is 100%, so the schema already documents both parameters' formats and behavior. The description adds no additional meaning to the input parameters beyond what is in 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 clearly states the tool searches for judicial process data by CNJ number, specifying it uses the DataJud API and returns metadata, class, subjects, court, parties, and movements. This distinguishes it from siblings like 'listar_processos_monitorados' or 'listar_tribunais'.
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 guidance on when to specify 'tribunal' vs omitting it, noting that omission triggers a slower search across all courts. It also mentions coverage of 91 courts, helping the agent decide context. No explicit when-not-to-use, but clear enough.
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?
No annotations are provided, so the description carries full burden. It discloses the implementation of legal articles (business days, start on next day, suspension during recess), offering algorithmic transparency. However, it does not mention whether the tool is read-only or any error conditions.
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 two sentences: the first clearly states the tool's function, and the second lists relevant legal articles. No redundant 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a complex purpose (deadline calculation with legal rules), and the description covers the algorithmic logic. With an output schema present for return format and full parameter documentation, it is mostly complete, though usage guidelines could be more explicit.
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 the input schema already documents all parameters. The tool description adds no additional parameter semantics beyond what is in the schema, so a baseline score of 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 clearly states the tool calculates the next procedural deadline in business days using the forensic calendar, which is a specific verb+resource combination. This distinguishes it from sibling tools like listar_processos_monitorados (list) and buscar_processo_por_numero (search by number).
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 implies usage for calculating deadlines but does not explicitly state when to use it vs alternatives or provide exclusions. While sibling tools are distinct, the lack of explicit guidance prevents a higher score.
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 must fully disclose behavior. It states the tool returns acronyms for use in other tools but does not describe the output structure or any side effects. Basic behavior is covered, but lacks depth.
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 with no wasted words. Front-loaded with the core purpose, followed by practical guidance.
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 zero parameters and a read-only list function, the description is reasonably complete. It explains the purpose and usage of the output. It could describe the output schema more, but that is likely covered separately.
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 tool has zero parameters, so schema coverage is 100% by default. The description adds value by explaining how the output connects to other tools, which is useful context beyond the empty input 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 clearly states the tool lists all supported courts, using a specific verb and resource. It distinguishes from sibling tools that deal with processes, not courts.
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 the returned acronyms can be used as the 'tribunal' parameter in other tools, implying when to use this tool. It does not provide explicit when-not conditions, but context is clear.
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 must convey behavior. It describes a read-only listing without side effects, but lacks details on authorization or session prerequisites.
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 and front-loaded, with two short sentences plus a returns line. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an existing output schema, the description provides sufficient context for a simple listing tool, including return format and next-step resource.
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?
The input schema has zero parameters, so no parameter explanation is needed. The description adds value by clarifying what the listing includes (snapshot in memory).
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 lists processes with snapshots in memory for the current session, distinguishing it from siblings like buscar_processo_por_numero and monitorar_processo.
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?
It indicates when to use (after snapshots have been saved) and directs to a resource for full data, but does not explicitly state when not to use or compare with alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses critical behaviors: dry-run mode by default, requirement for explicit confirmation, irreversibility, starts legal deadline, returns simulation if safety conditions not met. All behavioral traits are transparently stated.
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 well-structured with ASCII art and bullet points, front-loading the risk and purpose. It is longer than average, but every sentence is informative. Minor room for trimming, but the thoroughness is justified by the high-risk nature.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (high-risk, double gate, auth requirements), the description covers all necessities: use case, prerequisites, safety mechanism, output behavior (simulation vs real), and irreversibility. It is complete without needing output schema details.
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?
Schema coverage is 100%, yet the description adds significant value: 'confirmar' parameter is tied to the safety gate and operator awareness, 'id_intimacao' notes it comes from a sibling tool, and 'numero_processo' shows an example CNJ format. This goes well beyond the schema's brief 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 the tool confirms reading a judicial summons (intimação) via DJe, with specific verb ('confirmar') and resource ('leitura de intimação'). It distinguishes itself from siblings like 'listar_intimacoes' by emphasizing the irreversible legal effect, making its purpose unique and clear.
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 to use (confirming reading, with operator awareness of legal effect) and when not (for viewing only). It details prerequisites (environment variables) and the double safety gate, including that without 'confirmar=True' and the environment variable, only a simulation runs. This covers exclusions and alternatives implicitly.
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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