TCP Bolivia MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct search/retrieval operation: by party name, resolution number, free-text jurisprudence, full content, keyword-in-context, extracted sections, and PDF download. The purposes are clearly separated and unlikely to be confused.
Naming Consistency5/5All tool names follow a consistent pattern of a Spanish verb in imperative form followed by a descriptive noun phrase, using snake_case throughout. Variations like 'buscar_por_nombre' and 'buscar_jurisprudencia' are minor and still follow the verb-first convention.
Tool Count5/5Seven tools is within the ideal range for a focused domain. Each tool serves a clear, non-redundant purpose, and the count feels appropriate for a legal document search and retrieval server.
Completeness5/5The tool set covers the core lifecycle of searching and accessing resolutions: multiple search entry points, full-text retrieval, targeted extraction, and PDF download. There are no obvious dead ends for a read-only legal research workflow.
Average 3.8/5 across 7 of 7 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
This repository is licensed under MIT License.
This repository includes a README.md file.
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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 only states a search operation ('Busca') without explicitly confirming read-only behavior, describing return format, pagination, or potential limitations. This is minimal 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that immediately states the action and target. It wastes no words and is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one fully documented parameter, but the description does not specify what the search returns (e.g., case summaries, full listings) or any constraints like limits or authentication. The essential invocation info is present, but the lack of output details leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the single parameter 'nombre' with 'Nombre de la persona o parte a buscar'. The description's reference to 'partes involucradas' is essentially redundant with the schema, adding no new semantic detail beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Busca' (searches) and names the resource 'causas o expedientes en el TCP de Bolivia' with a clear criterion 'por el nombre de las partes involucradas'. This clearly distinguishes it from sibling tools like buscar_por_resolucion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for name-based searches but does not explicitly state when to use this tool over alternatives or provide exclusions. The phrase 'por el nombre de las partes involucradas' gives context but lacks explicit guidance such as 'use this when...' or 'instead of...'.
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 carries the full burden. It only states that it searches, without disclosing whether it returns a list, if matching is exact or partial, or any limitations or side effects. The example hints at accepted formats but doesn't describe output or error behavior. This is insufficient for a no-annotation context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with a clear example. It wastes no words and is front-loaded with the action verb.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool with 2 well-described parameters and no output schema, the description covers the input but omits return values and usage context relative to siblings. This leaves the agent uncertain about what to expect, though the low complexity mitigates the gap. The description is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with examples and 100% coverage. The tool description's example (Resolución 0601/2026-S2) reinforces the format but doesn't add meaningful new semantics beyond the schema. Thus, baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches resolutions by number and year, using a specific verb ('Busca') and resource ('resoluciones'). It distinguishes from siblings like buscar_por_nombre (which searches by name) and buscar_en_resolucion (which searches within a resolution).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case: when you have a resolution number and year, but does not explicitly compare with alternatives like buscar_por_nombre or buscar_en_resolucion. No exclusions or conditions are provided, leaving the agent to infer from the tool name. The example format helps but isn't explicit 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 bears full responsibility for behavioral disclosure. It does reveal meaningful traits: local processing on the PC and filtered output (only matching paragraphs with context). However, it omits details like case sensitivity, error handling, or output pagination, which would be useful for a complete picture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates purpose, method, and benefit. Every phrase earns its place, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter interface and absence of an output schema, the description sufficiently conveys the tool's behavior and rationale. It lacks details on edge cases or return format, but for a focused search tool, it is adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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. The description adds little beyond the schema, only referring to 'palabras clave' and 'contexto', which does not significantly deepen understanding of the parameters' exact semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for keywords within a TCP resolution, with a specific verb ('Busca') and resource ('resolución del TCP'). It also specifies the unique output behavior (returns only matching paragraphs with context), which distinguishes it from siblings like buscar_por_nombre or obtener_contenido_resolucion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied by the phrase 'para ahorrar tokens' and 'de forma local', suggesting this is for searching within an already identified resolution rather than fetching full content. However, there is no explicit mention of when to use it against alternatives, exclusions, or prerequisites.
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 shoulder behavioral transparency. It lacks any disclosure about return format, pagination, rate limits, authentication, or whether it's read-only. As a search tool, it might be inferred as read-only, but the description does not confirm that or add other behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly constructed sentence that front-loads the main verb and resource, immediately followed by the searching method and examples. Every word contributes to the tool's comprehension, with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter search tool, the description covers the scope and gives examples. However, since there is no output schema, it does not explain what the search returns (e.g., a list of resolutions, metadata, or just identifiers), leaving a gap for agents needing to parse results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents 'texto' as 'Texto legal o palabra clave a buscar'. The description adds value by providing concrete examples of valid inputs ('anticresis', 'asistencia familiar'), which clarifies the expected semantic types and enhances the schema's generic description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Busca' (searches) and the resources 'tesis de jurisprudencia y resoluciones' (jurisprudence theses and resolutions) via free text on legal topics. This distinguishes it from siblings like 'buscar_por_nombre' (search by name) and 'buscar_en_resolucion' (search within resolution), which focus on specific fields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: free text search on legal topics, with examples ('anticresis', 'asistencia familiar'). It implies a broad, keyword-based use case distinct from name/resolution-specific searches, though it doesn't explicitly state when not to use it or name alternatives.
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 returns the full resolution text, which is a meaningful behavioral trait. However, it does not describe the return format, potential errors, or authentication requirements, leaving some ambiguity for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence stating the action and resource, plus one sentence offering usage context. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, single-parameter tool with no output schema, the description is adequate: it states what it returns (the full text) and when to use it. It could be slightly more explicit about the exact output structure (e.g., a string vs. object), but overall it provides sufficient context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the only parameter (resolucionId) with 100% coverage. The description merely repeats 'por su ID (resolucionId)' without adding new meaning or constraints, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action and resource: 'Obtiene el texto de la resolución completa por su ID' (gets the complete resolution text by ID). It distinguishes itself from siblings like 'obtener_fundamentos_y_fallo' by specifying the entire text ('completa').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage context: 'Útil si deseas leer toda la sentencia' (useful if you want to read the whole ruling). It does not explicitly mention alternatives or exclusions, but the context is clear enough to guide selection.
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 of disclosing behavior. It explains that the tool filters and extracts specific sections, which implies a non-destructive read. It also notes token savings, adding useful context. However, it does not describe what happens if the sections are missing, the return format, or any access requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: the first states function and scope, the second highlights the token-saving benefit. There is no unnecessary repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (one parameter, no output schema), the description covers the core purpose and input requirement well. It would be slightly more complete if it described the return format or behavior when the ID is not found, but the current level is adequate for a straightforward extraction tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: the only parameter, resolucionId, is already described as the numeric ID. The tool description mentions 'en base a su ID', reinforcing but not adding new semantic meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Filtra y extrae') and a specific resource ('Fundamentos Jurídicos y el fallo final') from a sentencia based on its ID. It distinguishes from siblings like obtener_contenido_resolucion by emphasizing it extracts only a subset, and the token-saving benefit further differentiates it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys a clear use case: getting only the legal reasoning and final ruling while saving tokens. However, it does not explicitly mention when not to use the tool or name alternative tools, so it lacks explicit exclusionary guidance.
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 the full burden of behavioral disclosure. It proactively reveals that the file is saved to a specific location (Downloads folder) and notes the file's official digitally signed nature. However, it doesn't mention overwrite behavior or prerequisites, which is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, succinct sentence that front-loads the action and includes all essential information without any filler. It is perfectly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters and no output schema. The description adequately explains the core behavior (download and save location). It omits details about the return value or error handling, but given the low complexity and strong schema, this is not a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters (resolucionId and nombreArchivo) having clear descriptions in the input schema. The tool description adds no parameter-specific information, and per the rubric the baseline is 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool downloads the official digitally signed PDF of a resolution and saves it to the Downloads folder. This specific verb+resource combination distinguishes it from sibling tools that focus on searching or retrieving content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when the user needs to obtain the PDF file locally. While it doesn't explicitly name alternatives or exclusions, the sibling tools are all search/retrieve oriented, so the context is clear without needing explicit when-not guidance.
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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