airbyte-oss-mcp

Server Quality Checklist

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Latest release: v0.2.0
Disambiguation3/5
Tools are mostly distinct, but there is overlap among get_job, get_job_details, and get_job_failure_summary, which could confuse an agent about which to use. Additionally, get_active_syncs overlaps with list_jobs filtered by status. Descriptions help but ambiguity remains.
Naming Consistency4/5
Most tools follow a 'get_' or 'list_' pattern, but get_active_syncs uses 'get' for a list operation and find_duplicate_destination_tables uses 'find_', which is a minor deviation from the prevailing pattern.
Tool Count5/5
With 9 tools, the server is well-scoped for its intended purpose of monitoring and auditing Airbyte instances. Each tool has a clear role and no unnecessary redundancy.
Completeness2/5
The tool set is heavily biased towards read and monitoring operations, missing essential CRUD capabilities like creating or updating connections and triggering syncs. This leaves significant gaps for a full Airbyte management server.
Average 3.6/5 across 9 of 9 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- Last stable release on June 21, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
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{
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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?
With no annotations, the description bears full responsibility. It indicates a read operation ('Get') but does not disclose any behavioral traits such as idempotency, authentication needs, rate limits, or side effects. The minimal phrasing provides only a hint of safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundancy. It is front-loaded and efficient, though it sacrifices detail that could be included without bloat.
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 the tool has an output schema and two parameters (one undocumented), the description is insufficient. It does not explain what 'public job metadata' entails, nor does it cover the optional 'env' parameter. The output schema might compensate, but the description does not reference it or prepare the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It indirectly explains 'job_id' by stating 'for a sync job id', but it entirely omits the 'env' parameter, leaving its purpose unclear.
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 tool retrieves 'public job metadata' for a 'sync job id', using a specific verb and resource. However, it does not explicitly distinguish this from the sibling tool 'get_job_details', though the word 'public' suggests a subset.
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 'get_job_details' or 'list_jobs'. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states that the tool lists running syncs, without mentioning scope (e.g., per user or environment), side effects, permissions needed, or the meaning of the 'env' parameter. This lack of transparency limits agent understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very brief (three sentences) and front-loaded with the main purpose. However, it sacrifices important parameter information. It is concise but incomplete, earning a middle score.
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 the tool has one optional parameter and an output schema, the description should explain the 'env' parameter and the return value structure. It does neither, leaving the description incomplete for effective tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema contains one parameter, 'env', with no description in the schema (0% coverage) and no mention in the tool description. The description adds no meaning beyond the schema, leaving the agent uncertain about the parameter's purpose and usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's function: 'List all currently running sync jobs with connection names.' This is a specific verb and resource, and it distinguishes from sibling tools like list_jobs and get_job that have different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context by stating it is the 'Best tool to answer' specific questions about worker pool blocking or slow syncs. This implies when to use it but does not explicitly exclude alternative tools or mention 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully bears the burden. It discloses pagination behavior and case-insensitive filtering, but omits authentication, rate limits, or output shape details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: one sentence for purpose and a bullet list for filters. No wasted words; every sentence adds value.
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?
Covers key functions but does not explain the ordering or provide context for the 'env' parameter. With an output schema, missing return details are acceptable.
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 coverage is 0%, so description must compensate. It explains 4 of 5 parameters (name_prefix, status, limit, offset) with concrete details, but misses 'env' entirely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'List Airbyte connections with schedule and status metadata,' clearly specifying the verb and resource. It distinguishes from siblings like 'get_connection' (single) and 'list_jobs' (jobs).
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 filters but no explicit guidance on when to use this tool versus alternatives. It does not mention 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?
No annotations are provided, so the description carries the full burden. It mentions that job counts are from a 'recent sample,' which is a useful behavioral detail. However, it does not disclose whether the operation is read-only, requires special permissions, or has any side effects. The description adds some value but leaves 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?
Two sentences, front-loaded with the most important info ('Global Airbyte health snapshot. Start here for monitoring workflows.'). Every word earns its place; no wasted text.
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 (not shown), the description appropriately summarizes return values without repeating schema details. However, it omits any explanation of the 'env' parameter and does not clarify 'recent sample' bounds. Adequate but missing some context for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'env' with 0% description coverage, and the description does not mention this parameter at all. It adds no meaning beyond the schema, failing to compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's a 'Global Airbyte health snapshot' and lists specific return data (health text, workspace count, connection counts, job counts). It positions itself as the starting point for monitoring, distinguishing it from more specific sibling tools like get_connection or get_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Start here for monitoring workflows' explicitly guides when to use this tool—as a first check for overall health. It does not list exclusions, but the context from sibling tools implies alternatives for detailed views. A clear context is provided.
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, the description carries full burden. It discloses the tool is read-only ('get') and mentions the internal API endpoint, but does not discuss side effects, permissions, rate limits, or other behavioral traits. Adequate but not detailed.
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?
Two sentences, no wasted words. Front-loaded with purpose, followed by specific detail on includes/excludes. Excellent structure.
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 output schema exists (so return values are covered), the description covers the tool's purpose and main output. However, it omits the env parameter and does not mention any prerequisites or limitations beyond raw logs. Moderately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It implicitly references job_id via 'job', but completely fails to describe the 'env' parameter, leaving its purpose and valid values unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets job plus attempt stats, including per-attempt totalStats and failure summaries. It differentiates from siblings like get_job and get_job_failure_summary by specifying the inclusion of attempt statistics and exclusion of raw logs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool by stating what it includes (attempt stats and failure summaries) and excludes (raw logs). However, it does not explicitly name alternative tools or provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the tool returns root-cause failure messages from the latest failed attempt plus context and stats, but does not mention idempotence, permissions, or behavior when no failure exists. It is adequate but not thorough.
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 at two sentences, with the primary purpose front-loaded. Every sentence adds value, and there is no extraneous text.
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 presence of an output schema and no annotations, the description covers the essential purpose and output, but lacks parameter details and behavioral context like when to call this vs. raw logs. It is minimally complete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no information about the parameters (job_id and env). While parameter names are somewhat self-explanatory, the description fails to elaborate on their meaning or usage, leaving a gap for the AI agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it returns consolidated failure diagnosis for a sync job. It specifies the verb 'returns' and the resource 'failure summary', and distinguishes itself from raw logs and sibling tools like get_job or get_job_details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises 'prefer over raw logs', giving clear context for when to use this tool. It does not explicitly state when not to use it or mention alternatives, but the preference guidance is strong enough for most cases.
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 carries full burden. It discloses the tool is a 'best-effort audit' and specifies what it skips (non-BigQuery, inactive). This gives honest behavioral expectations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each adding value. The main action is first sentence, limitations follow. No unnecessary words.
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 has one optional parameter and a likely simple output (duplicate destinations), the description covers the main functionality and its caveats. It is sufficient for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description does not mention the single parameter 'env' or its purpose. The description adds no value over the schema for parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Detect' and clearly identifies the resource: 'multiple active connections writing the same BigQuery project.dataset.table'. This distinguishes it from sibling tools like list_connections and get_active_syncs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool's scope ('Best-effort audit using connection stream config and destination settings') and its limitations ('Skips non-BigQuery destinations and inactive connections'). It does not explicitly state when not to use or name alternatives, but the context is clear enough.
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?
The description discloses that it returns metadata with stream summaries and recent sync jobs, but does not cover error behavior (e.g., if connection not found), authorization requirements, or rate limits. Since no annotations are provided, the description carries full burden but offers only basic behavioral info.
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 two sentences long with no redundancy. The first sentence states the purpose and lookup method, the second describes the output. Every word adds value.
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?
The description sufficiently explains the tool's behavior for a simple get-by-ID operation. It identifies the lookup parameter and output shape. Although error handling and env parameter are missing, the presence of an output schema reduces the burden. Minor gap in not explaining the env parameter.
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 meaning to the 'connection' parameter by stating it can be an exact name or UUID, but does not explain the optional 'env' parameter. With 0% schema description coverage, the description partially compensates but leaves one parameter unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', the resource 'one connection', and the lookup criteria 'by exact name or connectionId UUID'. It also specifies the return value includes stream summaries and recent sync jobs, distinguishing it from siblings like list_connections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use this tool (to get a specific connection by name or UUID). It does not provide explicit when-not-to-use or alternatives, but the context of sibling tools is clear enough for an agent to differentiate.
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 carries the full burden. It discloses pagination behavior (limit, offset, and that it handles beyond 100-item pages) and the ordering. It does not explicitly state read-only nature or permissions, but the listing operation implies no side effects. The description is fairly transparent but could mention idempotency.
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 concise (approximately 6 sentences) and well-structured with a header line followed by a list of fields and then a bulleted filter list. No unnecessary words or redundancy.
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 presence of an output schema (context signals show it exists), the description's list of returned fields is helpful but not strictly required. It covers filters and pagination thoroughly. The missing 'env' parameter is a gap. Overall, it provides sufficient context for an agent to use the tool correctly.
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 coverage is 0%, so description must compensate. It explains connection, status, limit, and offset in detail, including format and constraints. However, it omits the 'env' parameter entirely. The explanation of connection's matching rule (exactly one) is valuable. Overall adds meaning but incomplete due to missing parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists recent sync jobs in newest-first order. It specifies the verb (list) and resource (sync jobs), and distinguishes from sibling tools like get_job (single job) and get_job_details (full details) by focusing on listing multiple jobs with key fields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use it (to list recent jobs) but does not explicitly contrast with alternatives like get_active_syncs or provide when-not-to-use guidance. The filtering options are described but no tactical advice on which tool to use for specific needs.
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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