Tribunal TJMG: Processo
Server Details
Tribunal TJMG: Court Case, official-source lookup. Platform-hosted, pay per query with prepaid credi
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/tribunal_tjmg_processo-mcp
- GitHub Stars
- 0
- Server Listing
- Tribunal TJMG: Processo
Available Tools
7 toolsauthenticateAIdempotentInspect
MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful behavioral context beyond the annotations by distinguishing permanent config-based auth from session-only login and by describing what the no-args call does. It does not contradict the idempotentHint, readOnlyHint, or destructiveHint annotations, though it could be more explicit about what state is stored when a token is pasted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, well-structured, and front-loaded with the primary action. Every sentence carries a distinct piece of information: the login flow, the configuration alternative, and the session-only invocation options.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple optional-token authentication tool with no output schema, the description covers the main invocation modes and server configuration path well. It does not explain failure or return-value details, but it is sufficient for an agent to correctly select and invoke the tool in common cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and this description fully compensates by documenting the token parameter as an optional JWT, showing the exact call shape, and explaining the no-args fallback. It directly tells the agent when token should be present and what to do if the user has not pasted it yet.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that this tool is for authentication/login for IDE agents by directing the user to log in via the browser, copy an access token, then either configure it or paste the token into the tool. This is specific enough to distinguish authentication from the listed sibling tools, especially 'connect'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly explains when to use which approach: adding the token to server config for a permanent, non-expiring connection, and pasting it into this tool for a session-only login. It also says that calling with no arguments returns the login link, which lets an agent choose the right invocation path.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
connectARead-onlyIdempotentInspect
Returns connection status and URLs. When all providers are connected, returns authenticated:true and empty pending[]. When credentials are missing, returns connect_url for the toolkit and per-install URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description details the behavior in both scenarios (all connected vs. missing credentials), specifying the return values. It is consistent with the readOnly and idempotent annotations, and no side effects are implied. This adds useful context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences that directly convey the purpose and behavior without redundancy. Every sentence contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description sufficiently explains the return values for both possible states. It provides a complete picture for a simple status-check tool, with no missing critical information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters in the input schema, and the description does not need to explain any. Since schema coverage is effectively 100% (no params), the baseline score of 3 is appropriate; the description adds no parameter-related details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool returns connection status and URLs, and distinguishes between the connected and missing-credentials cases. This clearly identifies the tool's purpose and differentiates it from sibling tools like authenticate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys when to use the tool (to check connection status) and outlines the two possible outcomes, but does not explicitly contrast with alternatives like authenticate. It is clear enough for most use cases but lacks explicit 'use this when' language.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
marketplaceAInspect
The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| action | No | search | |
| mcp_id | No | ||
| message | No | ||
| tool_id | No | ||
| arguments | No | {} | |
| immediate | No | ||
| tier_slug | No | ||
| prompt_body | No | ||
| prompt_slug | No | ||
| prompt_tool | No | ||
| prompt_vars | No | {} | |
| conversation | No | [] | |
| prompt_title | No | ||
| request_name | No | ||
| cancel_reason | No | ||
| cancel_comment | No | ||
| prompt_targets | No | ||
| report_context | No | ||
| prompt_category | No | ||
| request_details | No | ||
| prompt_description | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Even with annotations indicating readOnlyHint=false, the description adds substantial context: invoke runs one-off without installing, may return connect/checkout links, and writes require workspace owner/admin. It explains side effects (e.g., 'without bloating the tool list') and permission requirements, going far beyond the structural annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Despite containing a wealth of accurate information, it is delivered as one massive, unstructured wall of text with no line breaks, bullet points, or headers. While front-loaded with a strong opening sentence, the density makes it difficult for an agent to quickly extract key details. The information could be reorganized into sections (e.g., core flow, invoke behavior, prompt library) for better scannability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (23 parameters, 14+ actions), the description covers all major aspects: search/discovery, execution, installation, auth flows, payment handling, permission model, prompt library, and fallback mechanisms. It explains the full lifecycle from discovery to execution to management, making it a comprehensive reference for a highly complex meta-tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description carries the full burden and excels: it explains the meaning of the action enum values (search, describe, install, invoke, etc.) and the relationships between mcp_id, tool_id, and arguments. It clarifies the prompt library parameters (search_prompts, get_prompt, publish_prompt) and their purpose, compensating for the lack of schema-level documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description immediately identifies the tool as 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly distinguishes itself from siblings by describing its core flow (search → describe → invoke) and explicitly contrasts with alternatives like report_bug and request_mcp. The verb+resource is specific and the tool's role as a catalog and execution engine is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit decision guidance: 'Use install only to make an MCP PERMANENT in the active toolkit' and 'prefer invoke for a single/occasional use.' It also gives when-not-to-use guidance (e.g., 'if nothing fits' for request_mcp) and describes when prompt library actions are appropriate. This is a model example of usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_bugAIdempotentInspect
Report a bug, missing feature, or send feedback. Include the conversation array with recent messages for reproduction.
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | ||
| message | Yes | ||
| conversation | No | [] |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds some behavioral context by recommending including the conversation array for reproduction, which is useful for understanding what input helps. It does not disclose potential state changes or side effects, and there is no contradiction with the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, both relevant. It front-loads the purpose and provides one key usage tip. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, and the description covers the primary purpose and one important parameter interaction. It misses some detail (e.g., what 'context' is for), but with a required message parameter and optional conversation, the description is adequate for typical usage. The lack of an output schema keeps expectations minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the parameter burden. It clarifies the 'conversation' parameter as an array for reproduction, but it does not explain 'message' (which is required) or the 'context' parameter. The description adds partial value but does not fully compensate for the missing schema documentation, especially since it implies 'conversation' might be required, contradicting the schema's required field.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose clearly: 'Report a bug, missing feature, or send feedback.' It uses a specific verb (report) and a clear resource (bugs, feature requests, feedback). This is distinct from all sibling tools, which focus on authentication, connections, marketplace, version checks, toolkits, and tribunal processes—none of which overlap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises to 'Include the conversation array with recent messages for reproduction,' which is basic usage guidance but does not explicitly state when to use this tool versus alternatives. There are no explicit when/when-not or alternative recommendations. The purpose implies usage for bug reporting, but it does not contrast with other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
show_versionARead-onlyIdempotentInspect
Show the current MCP platform and adapter versions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, providing the safety profile. The description adds no behavioral context beyond naming the returned information, so it neither enriches nor contradicts the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no extra words. It front-loads the verb and specifies exactly what version categories are shown, achieving maximum clarity in minimal space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, read-only tool with strong annotations, the description is fully sufficient. There is no output schema or complex behavior to document, so nothing is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the schema provides complete coverage trivially. The description doesn't need to explain parameters, and the baseline for 0 params is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Show the current MCP platform and adapter versions.' This clearly distinguishes it from sibling tools like authenticate, connect, marketplace, report_bug, and tribunal_tjmg_processo_consultar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended usage is clear: call this tool when you need current MCP platform and adapter version information. It does not explicitly name alternatives, but for a zero-parameter informational tool, no exclusion guidance is necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
toolkit_infoARead-onlyIdempotentInspect
Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful behavioral context by specifying the exact scope of the returned state (installed MCPs, statuses, accounts, tool counts), which goes beyond the annotations by detailing what the 'toolkit state' includes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the purpose and packs all relevant details without redundancy. Every clause adds value, and there is no unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and a clear read-only purpose, the description fully enumerates the expected return content. It answers what information is available, which is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and per the rubric the baseline is 4. The description fully communicates what the tool does without needing to explain any parameter meanings; there is nothing missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state'), enumerating the exact information provided: installed MCPs, connection status, connected accounts, and number of catalog tools. This distinguishes it from sibling tools like authenticate or connect, which are action-oriented rather than informational.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as a read-only diagnostic/inspection tool, but it does not explicitly state when to use it versus alternatives or provide exclusion criteria. An agent can infer its purpose from the name and content, but there is no direct guidance on when it should be preferred over other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tribunal_tjmg_processo_consultarARead-onlyIdempotentInspect
Tribunal TJMG: Processo, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| cpf | No | ||
| cnpj | No | ||
| nome_parte | No | ||
| nome_advogado | No | ||
| numero_processo | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond the annotations: the payment model ('pague por consulta com crédito pré-pago'), the fact that no platform credentials are needed, the non-confidential nature of the data ('não é dado sigiloso'), and LGPD compliance responsibilities. These details meaningfully enrich the agent's understanding of the tool's operational and legal behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise and front-loaded with the core purpose in the first sentence. The remaining sentences add valuable context about hosting, credentials, payment, data sensitivity, and legal responsibility. It is slightly dense but every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's source, access model, payment, data confidentiality, and legal liability, which is quite complete for a read-only consultation tool. However, it does not describe the output format or clarify how the five optional parameters should be combined, leaving a minor gap given that no output schema is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage and the tool description provides no parameter-level guidance, such as which identifiers are required, whether they are alternatives or complementary, or formatting expectations. The parameter names (cpf, cnpj, nome_parte, nome_advogado, numero_processo) are self-explanatory, but the description does not compensate for the complete lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a consultation ('consulta') of judicial processes at the TJMG court using an official source ('Tribunal TJMG: Processo, consulta em fonte oficial'). This is a specific verb + resource pair, and the purpose is unambiguous despite the lack of sibling judicial tools to differentiate from.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: it accesses official Brazilian public data, requires no platform credentials, and is paid per query with prepaid credits. It does not explicitly name alternatives or exclusions, but the sibling tools are unrelated platform utilities, so no direct alternative guidance is necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
No tool schema history has been recorded yet.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
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Feature your server to boost visibility and reach more users
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Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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For server owners:
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Several tools overlap in purpose: authenticate and connect both handle authentication/connection, while marketplace and toolkit_info both relate to MCP management. The legal query tool is isolated, but the MCP management tools have blurred boundaries.
Tool names are wildly inconsistent: mix of verbs (authenticate, connect, report_bug), nouns (marketplace, toolkit_info), and a Portuguese phrase (tribunal_tjmg_processo_consultar). No clear pattern or verb-noun structure.
While 7 tools is within the typical range, the set is not well-scoped—it combines MCP management utilities with a single domain-specific query, making the purpose diffuse and the number neither minimal nor cohesive.
The server appears to serve two disparate domains: MCP management (missing many standard operations) and Brazilian legal process consultation (only one query tool). Neither domain is covered comprehensively, leaving obvious gaps.