Telegram Bridge MCP
Server Quality Checklist
Latest release: v7.9.0
- Disambiguation4/5
Most tools have distinct purposes: action dispatches commands, dequeue consumes updates, help provides documentation, send transmits messages. However, send overloads multiple sending modes (notify, send_file, etc.) which could cause confusion.
Naming Consistency2/5Tool names are inconsistent: two verbs (dequeue, send), one noun (action), and one ambiguous (help). No consistent pattern like verb_noun or camelCase.
Tool Count3/5Four tools is minimal but acceptable for a simple bridge. The scope seems intentionally limited, but more tools might be expected for a full-featured bridge.
Completeness3/5Core send and receive operations are covered via send and dequeue. Session management is handled through action. However, missing editing, deleting, or searching messages leaves notable gaps.
Average 4.3/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 96 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the different behaviors based on topic, but does not explicitly state that the tool is read-only or has no side effects. The schema mentions an 'identity' topic not covered in the description, creating 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 extremely concise, using two sentences to convey all necessary information. It front-loads the purpose and uses bullet-like notation for clarity.
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 of the help tool, the description covers most usage scenarios. It lacks mention of the 'identity' topic (present in schema), and does not describe return format, but for a help tool this is acceptable.
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 provides detailed descriptions for both parameters (topic and token) with 100% coverage. The description adds little beyond restating the options; it does not provide additional parameter semantics that the schema lacks.
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 as 'Discovery for this MCP server' and specifies distinct behaviors for different inputs (no args, 'index', 'guide', tool name). This clearly distinguishes it from siblings (action, dequeue, send) which are likely operational tools.
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 explicit guidance on when to use each variant (overview, index, guide, detailed help). While it does not explicitly mention when not to use it, the context makes it obvious that help is for information and not for performing actions.
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?
Without annotations, the description carries full burden. It explains the three modes and token requirements but does not disclose error handling, rate limits, side effects (e.g., destructive actions like shutdown), or return value structure. This limits transparency.
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 (two sentences plus a reference) and front-loaded with the core concept. No wasted words, making it efficient for agent parsing.
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 complexity (80 parameters, no output schema, no annotations), the description provides sufficient context for basic usage but relies on 'help(topic: action)' for full documentation. It lacks details on output, error cases, and state changes, making it somewhat incomplete.
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 parameters are already described. The description adds a high-level structure (modes) but does not elaborate on individual parameters beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as a universal action dispatcher with three distinct modes: listing all categories (omit type), listing sub-paths (pass category), and executing actions (pass full path). This specificity differentiates it from sibling tools like dequeue, help, and send.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use each mode and references help(topic: 'action') for full documentation, providing a clear alternative. It also implicitly excludes other tools by focusing on action dispatching.
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?
With no annotations, the description must disclose behaviors. It explains auto-split, Markdown, TTS configuration requirement, and captioning for voice notes. However, it omits details like error handling, side effects (message sent), and permission requirements, leaving some gaps for a complex tool.
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 front-loaded with core purpose and uses a clear arrow-format for modes. It is concise but covers essential guidance. A slightly more structured layout could improve readability, but currently it is efficient with no wasted sentences.
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 tool's complexity (47 params, no output schema, no annotations), the description covers main modes and sibling differentiation. It misses some context like default behaviors for complex interactions, but overall provides sufficient context for an AI agent to understand primary usage.
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 each parameter has a description in the schema. The tool description adds value for key params (text, audio) but does not elaborate on many others. Baseline of 3 is appropriate as the schema already handles parameter 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's core function: sending messages as text, audio, or both. It details the three modes (text-only, audio-only, both) and distinguishes from sibling tools like notify, send_file, and interactive prompts, providing a specific verb+resource description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to use this tool vs alternatives: 'For structured status, use notify. For file attachments, use send_file. For interactive prompts, use ask, choose, or confirm.' Also advises to call with no args to see available types, covering both when to use and how to explore.
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?
With no annotations provided, the description fully carries the burden of behavioral disclosure. It details the order of event draining, all possible return shapes (updates, pending, timed_out, error), default wait behavior, hard cap, force override, and duplicate-session detection. No contradictions with annotations (none exist).
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 front-loaded with the core purpose and return types, followed by detailed but necessary behavioral notes. It is dense with information yet remains clear. Minor redundancy (e.g., mentioning 'call again' multiple times) could be trimmed, but overall it is well-structured and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema, no annotations), the description covers all aspects: return types, error handling, default values, alternative actions, and optional features. It is comprehensive enough for an AI agent to understand and invoke the tool correctly without needing external references.
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?
Although the schema already has 100% coverage, the description adds significant context beyond the schema: the meaning of max_wait omission (session default), the fallback value, the force parameter's relationship to the default, the purpose of connection_token for duplicate detection, and the effect of response_format. This extra value justifies a score above the baseline of 3.
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 ('Consume queued updates') and the resource ('queued updates'), with specific detail on event processing order (non-content events first, then up to one content event). It is easily distinguished from sibling tools like action, help, and send.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to call again (pending > 0), when to stop (session_closed error), and how to raise the default wait via action(type: 'profile/dequeue-default'). It also directs users to call help(topic: 'dequeue') for more details, covering both usage and alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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