Airtable OAuth MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no ambiguity: create_record vs create_records handles single vs batch creation, list_records vs search_records provides listing vs filtered searching, and get_record vs update_records vs delete_records covers different CRUD operations. The descriptions reinforce these distinctions, making tool selection straightforward.
Naming Consistency5/5
All tools follow a consistent verb_noun naming pattern using snake_case (e.g., create_record, list_bases, update_records). The verbs are appropriate and predictable (create, delete, describe, get, list, search, update), creating a coherent and readable toolset.
Tool Count5/5
With 10 tools, this server is well-scoped for Airtable operations. Each tool earns its place by covering essential CRUD operations, base/table management, and search capabilities. The count is neither too sparse nor bloated, fitting typical agent workflows effectively.
Completeness5/5
The toolset provides complete coverage for Airtable interactions: CRUD operations on records (create, get, update, delete, list, search), base and table management (list_bases, list_tables, describe_table), and support for both single and batch operations. There are no obvious gaps that would hinder agent workflows.
Average 3/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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 passing
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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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}
```
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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 full burden. 'Update multiple records' implies a batch mutation operation, but it doesn't disclose permissions needed, whether updates are atomic, error handling, rate limits, or what happens on partial failures. This is inadequate for a mutation tool with zero annotation coverage.
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 extremely concise with just three words, front-loaded with the core action. There's no wasted language, though this conciseness comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations, 4 parameters, and an output schema exists, the description is incomplete. It doesn't explain the update mechanism, constraints, or what the output might contain. The existence of an output schema helps but doesn't compensate for the lack of behavioral context in the description.
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 schema already documents all parameters. The description adds no additional meaning beyond implying batch updates through 'multiple records', which is redundant with the 'records' array parameter in the schema. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update multiple records' clearly states the verb (update) and resource (records), but it's vague about scope and doesn't distinguish from siblings like 'create_record' or 'delete_records'. It doesn't specify what kind of records or system is involved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites, when to choose this over single-record updates, or how it relates to siblings like 'create_records' or 'delete_records'.
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, the description carries full burden but only states the action ('create') without disclosing behavioral traits like permissions needed, whether it's idempotent, error handling, or response format. It mentions 'single record' which hints at scope 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?
The description is extremely concise ('Create a single record') with no wasted words, front-loaded and to the point. It's efficient, though this brevity contributes to gaps in other dimensions.
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 a mutation tool with no annotations but a rich input schema (4 params, 100% coverage) and an output schema (implied by context signals), the description is minimal. It covers the basic action but lacks details on behavior, usage, or output, making it adequate but incomplete for full agent understanding.
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 schema fully documents parameters like 'base_id', 'table_id', 'fields', and 'typecast'. The description adds no extra meaning beyond implying a single record creation, aligning with the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a single record' clearly states the verb ('create') and resource ('record'), but it's vague about the context (Airtable) and doesn't distinguish from siblings like 'create_records' (plural vs. single). It's functional but lacks specificity and differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'create_records' or 'update_records', nor does it mention prerequisites or context. It's a bare statement with no usage instructions.
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. 'Create multiple records' implies a write operation but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just three words, front-loaded with the key action. Every word earns its place, and there's no wasted text, making it efficient for quick understanding.
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 (which covers return values), 100% schema description coverage, and no annotations, the description is minimally adequate but lacks depth. For a mutation tool that creates multiple records, it should provide more context on usage, behavior, and differentiation from siblings to be fully complete.
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 schema already documents all parameters (base_id, table_id, records, typecast) with descriptions. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints. 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create multiple records' clearly states the action (create) and resource (records), but it's vague about the scope and doesn't distinguish from its sibling 'create_record'. It doesn't specify what kind of records or in what system, though context suggests Airtable. It's functional but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like 'create_record' (for single records) or other siblings. The description doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.
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 full burden but only states the basic action without behavioral details. It doesn't mention whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or what happens with invalid formulas. For a search tool with 5 parameters, this is insufficient disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a tool with good schema documentation and gets straight to the point without unnecessary elaboration.
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 (which handles return values) and 100% schema coverage, the description is minimally adequate. However, for a search operation with formula filtering and multiple sibling tools, it should provide more context about when to use it and what behavioral expectations exist, especially with no annotations.
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%, providing good documentation for all parameters. The description adds minimal value by mentioning 'formula filter' which aligns with the 'filter_by_formula' parameter but doesn't explain formula syntax or provide examples. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search records using a formula filter' states the verb (search) and resource (records) but is vague about scope and lacks differentiation from sibling tools like 'list_records' or 'get_record'. It doesn't specify what type of records or system is involved, though the input schema hints at Airtable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like 'list_records' or 'get_record'. The description implies formula-based filtering but doesn't explain when this is preferred over other filtering methods or tools, leaving the agent to guess based on parameter names alone.
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 full burden. It states the action is deletion, implying a destructive mutation, but doesn't disclose behavioral traits like whether deletions are permanent, require specific permissions, have rate limits, or what happens on partial failures. This is inadequate for a destructive tool with zero annotation coverage.
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 extremely concise with a single sentence ('Delete multiple records'), front-loaded and zero waste. Every word earns its place by directly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a destructive mutation tool with no annotations, 100% schema coverage, and an output schema exists, the description is incomplete. It fails to address critical context like safety warnings, error handling, or output expectations, leaving gaps despite structured data covering parameters and outputs.
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 schema already documents all three parameters (base_id, table_id, record_ids) with descriptions. The description adds no additional meaning beyond what the schema provides, such as format details or usage examples, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and resource ('multiple records'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'update_records' or 'create_records' beyond the deletion action, missing explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like 'update_records' for modification or 'list_records' for viewing. The description lacks context about prerequisites, such as needing existing records to delete, or exclusions like when not to use it.
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 states this is a list operation with filtering, but doesn't mention whether it's read-only, pagination behavior, rate limits, authentication requirements, or what happens when no records match. For a tool with 6 parameters and no annotations, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point. It's appropriately sized for a list operation and wastes no words. Every part of the description earns its place by conveying the core functionality.
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 (which means return values are documented elsewhere) and 100% schema coverage, the description is minimally adequate. However, for a tool with 6 parameters and no annotations, it should provide more behavioral context about how filtering works, pagination, or when to use versus sibling tools to be truly complete.
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 schema already documents all parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions 'optional filtering' which aligns with parameters like 'filter_by_formula' and 'view', but doesn't provide additional context or usage examples. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('records from a table'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'search_records' or 'get_record', which likely have overlapping functionality for retrieving records.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'optional filtering' but provides no guidance on when to use this tool versus alternatives like 'search_records' or 'get_record'. There's no mention of prerequisites, limitations, or specific use cases that would help an agent choose between these sibling tools.
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. It states the action ('List tables') but lacks critical details: whether this is a read-only operation (implied but not explicit), if it requires authentication, pagination behavior, rate limits, error handling, or what the output contains (though an output schema exists). For a tool with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence ('List tables in a specific base') that is front-loaded with the core action and resource. It wastes no words, avoids redundancy, and is appropriately sized for a simple listing tool. Every part of the sentence earns its place by specifying scope ('in a specific base').
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's low complexity (listing operation), high schema coverage (100%), and presence of an output schema (which handles return values), the description is minimally complete. However, it lacks context on authentication, error cases, or sibling differentiation, which could aid the agent. It's adequate but leaves gaps that the agent must bridge with external knowledge or trial.
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%, with both parameters well-documented in the schema (base_id as 'Airtable base ID', detail_level with enum values and default). The description adds no additional parameter semantics beyond implying a 'specific base' context for base_id. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, though the description doesn't compensate or enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('tables in a specific base'), making the purpose immediately understandable. It distinguishes from siblings like 'list_bases' (which lists bases) and 'describe_table' (which provides detailed table metadata). However, it doesn't explicitly mention the Airtable context or differentiate from 'list_records' (which lists records within tables), leaving room for slight ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a base ID), contrast with 'list_bases' (for listing bases) or 'describe_table' (for detailed table info), or specify use cases like exploring base structure. The agent must infer usage from the name and parameters alone.
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 'Get detailed information' implies a read operation, it doesn't specify whether this requires authentication, what format the information returns in, potential rate limits, or error conditions. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple read operation and front-loads the core functionality. Every word earns its place in this concise formulation.
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 relative simplicity (2 required parameters), 100% schema coverage, and the presence of an output schema (which handles return values), the description is reasonably complete. It states the core purpose clearly. However, it could better address behavioral aspects given the lack of annotations, and usage guidance is minimal.
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?
The description adds no parameter-specific information beyond what's already in the schema (which has 100% coverage). It doesn't explain what 'detailed information' includes, how table_id can be specified (ID vs name), or provide examples. With complete schema documentation, the baseline is 3, but the description doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'detailed information about a specific table', making the purpose understandable. It distinguishes from siblings like list_tables (which lists tables) and get_record (which gets records), but doesn't explicitly contrast with them. The description is specific enough to understand what the tool does without being tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate versus list_tables (for listing tables) or get_record (for getting record data), nor does it provide any context about prerequisites or typical use cases. The agent must infer usage from the tool name and description alone.
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. It states the action ('Get') but doesn't describe whether this is a read-only operation, what happens if the ID is invalid (e.g., error handling), or any rate limits or authentication requirements. For a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple lookup tool, making it easy to parse and understand quickly.
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 low complexity (a simple read operation), 100% schema coverage, and the presence of an output schema, the description is reasonably complete. It clearly states what the tool does, though it lacks behavioral details that would be helpful without annotations. The output schema likely covers return values, reducing the need for that in the description.
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?
The schema description coverage is 100%, with all three parameters clearly documented in the input schema. The description adds no additional meaning beyond what the schema provides, such as explaining the relationship between base_id, table_id, and record_id. However, since the schema does the heavy lifting, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'a specific record by ID', making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'list_records' or 'search_records', but the 'by ID' specification implies a direct lookup rather than filtering or listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_records' or 'search_records'. It doesn't mention prerequisites, such as needing to know the exact record ID, or exclusions, such as not being suitable for bulk operations. Usage is implied but not explicitly stated.
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 states what the tool does but doesn't describe any behavioral traits such as pagination, rate limits, sorting, or what 'accessible' means in terms of permissions. This leaves significant gaps for an agent to understand how to use it effectively.
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 a single, clear sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and efficiently communicates the core functionality, making it easy for an agent to parse quickly.
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 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks context about when to use it, behavioral details, and differentiation from siblings, which are important for a list operation in a server with multiple listing tools. The output schema helps, but the description should do more to guide usage.
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 input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here, but it doesn't compensate for any gaps since there are none. A baseline of 4 is given as it's complete for a no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'all accessible Airtable bases', making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_tables' or 'list_records', which would require mentioning it's about bases rather than tables or records.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), context for when listing bases is appropriate, or how it differs from related tools like 'list_tables' or 'describe_table'.
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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Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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