DB Timetable MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: findStations searches for stations, getCurrentTimetable retrieves real-time data, getPlannedTimetable fetches future schedules, and getRecentChanges tracks recent changes. There is no overlap in functionality, making tool selection straightforward for an agent.
Naming Consistency4/5The naming follows a consistent verb_noun pattern with three tools starting with 'get' and one with 'find', all using camelCase. The minor deviation is 'findStations' versus 'getX', but it remains readable and predictable.
Tool Count5/5With 4 tools, the server is well-scoped for its purpose of accessing railway timetable data. Each tool serves a specific and necessary function, providing a focused set without being too sparse or overwhelming.
Completeness4/5The tool set covers core operations for timetable data: searching stations, retrieving current and planned schedules, and tracking changes. A minor gap is the lack of tools for modifying or managing data (e.g., CRUD operations), but this may be intentional for a read-only server, and agents can work around this limitation.
Average 3.4/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 3 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 failing
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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the search functionality and return type (list of stations) but lacks details on permissions, rate limits, error handling, or whether it's a read-only operation. For a search tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 and well-structured in three sentences: it states the action, explains the parameter, and describes the output. Every sentence adds value without redundancy, making it efficient and front-loaded.
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 tool's moderate complexity (search with one parameter) and no annotations or output schema, the description is minimally adequate. It covers the basic purpose and parameter but lacks details on behavioral traits, usage context, and output format. It meets the minimum viable standard but has clear 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 description coverage is 100%, so the schema already fully documents the single parameter 'pattern'. The description adds minimal value by mentioning it can be a station name or EVA number, which is already implied in the schema's example. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: searching a directory of railway stations using a search pattern (station name or EVA number) and returning a matching list. It specifies the resource (station directory) and verb (search), but doesn't explicitly differentiate from sibling tools like timetable or change queries, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description explains what it does but doesn't mention when it's appropriate compared to sibling tools (getCurrentTimetable, getPlannedTimetable, getRecentChanges) or any other search methods. There's no context about prerequisites or exclusions.
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 of behavioral disclosure. While it indicates this is a read operation for retrieving data, it doesn't disclose important behavioral traits such as whether the tool requires authentication, has rate limits, what format the returned data takes, or whether it supports pagination for large result sets. The description adds minimal behavioral context beyond the basic retrieval function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences that each serve a purpose: the first states the core functionality, the second provides usage context. It's front-loaded with the main purpose and avoids unnecessary elaboration. While efficient, it could potentially be slightly more concise by combining the two sentences.
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 read-only tool with 3 well-documented parameters and no output schema, the description provides adequate but incomplete context. It covers the basic purpose and usage scenario but lacks important details about the return format, error conditions, and behavioral constraints. Without annotations or output schema, the description should do more to help an agent understand what to expect from the tool's execution.
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 has 100% description coverage with clear parameter documentation including examples and format specifications. The description doesn't add any meaningful parameter semantics beyond what's already in the schema - it merely restates that parameters are for station, date, and hour without providing additional context or clarification. With complete schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: retrieving planned timetable data for a specified train station, date, and hour. It uses specific verbs ('holt...ein' - fetches/retrieves) and identifies the resource ('Fahrplandaten' - timetable data). However, it doesn't explicitly differentiate from sibling tools like getCurrentTimetable, which appears to serve a similar function but for current rather than planned data.
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 provides implied usage context by stating the tool is useful for planning schedules in advance and obtaining information about future train connections. However, it doesn't explicitly state when to use this tool versus alternatives like getCurrentTimetable or findStations, nor does it mention any prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions real-time updates and lists types of changes (delays, track changes, cancellations), but doesn't address critical aspects like rate limits, authentication requirements, data freshness guarantees, or error conditions. For a real-time data tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences that efficiently convey the tool's purpose and scope. The first sentence states the core function, and the second elaborates on what's included and the real-time nature. There's minimal wasted verbiage, though it could be slightly more structured.
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 tool's moderate complexity (real-time operational data), no annotations, and no output schema, the description provides adequate basic context but lacks completeness. It covers what data is retrieved but doesn't address format, pagination, error handling, or limitations. The absence of output schema means the description should ideally explain return values, which it doesn't.
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 description coverage is 100% with the single parameter 'evaNo' well-documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Ermittelt die neuesten Fahrplanänderungen für eine spezifische Bahnhofsstation' (retrieves the latest schedule changes for a specific train station). It specifies the verb 'ermittelt' (retrieves) and resource 'Fahrplanänderungen' (schedule changes), and distinguishes from siblings by focusing on real-time operational adjustments rather than station lookup or timetable retrieval.
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 context by mentioning 'Echtzeit aktualisiert werden' (updated in real-time), suggesting this tool is for current operational changes rather than planned timetables. However, it doesn't explicitly state when to use this tool versus alternatives like getCurrentTimetable or getPlannedTimetable, nor does it provide exclusions or prerequisites.
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 this is a read operation (retrieves data) and specifies what data is included (arrival/departure times, platform assignments, delays, real-time info). However, it doesn't mention potential limitations like rate limits, authentication needs, or 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences that efficiently convey the tool's purpose and scope. The first sentence states the core function, and the second elaborates on what data is included. No wasted words, though it could be slightly more front-loaded.
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 single-parameter read tool with no annotations and no output schema, the description provides adequate context about what data is returned. However, it doesn't describe the return format, potential pagination, or error handling, which would be helpful given the lack of structured output documentation.
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 has 100% description coverage, with the evaNo parameter well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3 for high schema coverage.
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 specific action ('Ruft die aktuellen Fahrplandaten ab' - retrieves current timetable data) and resource ('einer bestimmten Bahnhofsstation' - of a specific railway station). It distinguishes from siblings by specifying it's for current/real-time data (vs. planned timetable or station search).
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 about when to use this tool - for current timetable data with real-time information for the current operating day. It doesn't explicitly state when NOT to use it or name alternatives, but the context strongly implies this is for real-time vs. planned data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/jorekai/db-timetable-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server