AppFlowy Cloud MCP Server

by Jemo69

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific resources and actions - authentication (login/refresh), workspace listing, database operations, and row CRUD. There's no overlap or ambiguity between tools like list_databases vs list_rows or create_row vs upsert_row.
Naming Consistency5/5
All tools follow a perfect 'appflowy_verb_noun' pattern consistently throughout. The naming convention is uniform with clear action-object relationships, making the tool set predictable and easy to understand.
Tool Count5/5
With 9 tools, this server provides comprehensive coverage for AppFlowy Cloud operations without being overwhelming. The count is well-scoped for database/workspace management with authentication support, making each tool earn its place.
Completeness4/5
The tool set covers authentication, workspace listing, database discovery, and full row CRUD operations with upsert capability. The only minor gap is the lack of explicit database/workspace creation/deletion tools, but agents can still accomplish core workflows with the available operations.
Average 2.6/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 2 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
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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 must carry the full burden. While 'Create' implies mutation, the description discloses nothing about return values, error handling (e.g., duplicate keys), whether the operation is atomic, or what the 'document' field represents.
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 brief (6 words), but given the tool's complexity (nested objects, 3 undocumented parameters, mutation behavior), this brevity constitutes underspecification rather than efficient communication. It is not front-loaded with actionable guidance.
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?
Inadequate for the structural complexity. The tool has nested objects (request containing cells), no output schema, and no annotations. The description should explain the relationship between workspace/database hierarchies and the cells format, but provides none of this context.
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?
With 0% schema description coverage, the description completely fails to compensate. It provides no explanation of what workspace_id or database_id refer to, nor the structure expected within the nested 'cells' object (which accepts 'additionalProperties: true').
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 states the core action ('Create') and resource ('row in a database'), but fails to differentiate from the sibling tool 'appflowy_upsert_row'. It essentially restates the tool name with minimal additional context, leaving ambiguity about when to prefer create over upsert.
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 provided on when to use this tool versus alternatives (specifically appflowy_upsert_row), nor any mention of prerequisites like obtaining workspace_id/database_id from the list_workspaces or list_databases 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 full burden. It does not disclose what the 'fields' contain (names, types, constraints?), the return format, or whether this is a read-only operation (though implied by 'Get'). No mention of pagination, rate limits, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundancy. However, it is arguably under-specified rather than appropriately concise given the lack of schema documentation and annotations.
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 0% schema coverage, no annotations, and no output schema, the description provides insufficient context. For a tool requiring hierarchical identifiers (workspace → database), it should explain the parameter dependencies and what constitutes a 'field' in AppFlowy's data model.
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%, so the description must compensate. It mentions 'specific database' which loosely implies the database_id parameter, but completely omits workspace_id. No explanation of parameter formats, valid values, or hierarchical relationship between workspace and database is provided.
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 states the basic action ('Get fields') and target ('specific database'), but borders on tautology with the tool name 'appflowy_get_database_fields'. It does not clarify whether 'fields' refers to column schema/definitions or something else, though the sibling tool 'appflowy_list_rows' implies this is metadata rather than data.
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 provided on when to use this versus sibling tools like 'appflowy_list_databases' or 'appflowy_get_row_details'. Crucially, it fails to mention that users must first call 'appflowy_list_workspaces' and 'appflowy_list_databases' to obtain the required workspace_id and database_id parameters.
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 responsibility for behavioral disclosure. It fails to mention what 'with_doc' implies (likely including associated document content), error behavior for missing IDs, or whether this is a read-only operation (implied by 'Get' but not explicit).
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?
Extremely brief at 7 words. While it wastes no words and uses active voice, it is under-specified for the tool's complexity. However, the single sentence is appropriately structured with the verb front-loaded.
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?
Inadequate for a 4-parameter tool with zero schema documentation and no output schema. The description omits return value structure, the relationship between rows and documents (with_doc), and hierarchical context (workspace/database). Needs significant expansion to be usable.
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?
With 0% schema description coverage, the description must compensate by explaining all 4 parameters. It only implicitly references row_ids via 'IDs'. It fails to explain: workspace_id/database_id (hierarchy/context), row_ids format (comma-separated? JSON array?), or with_doc behavior. Critical gap given the schema lacks descriptions.
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?
States the basic action ('Get details') and resource ('rows'), and includes 'by IDs' which helps distinguish from the sibling appflowy_list_rows. However, 'details' is vague (what fields are returned?) and it doesn't clarify the AppFlowy-specific context (databases, workspaces).
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?
Provides no guidance on when to use this versus list_rows (filtering vs. specific ID lookup) or prerequisites (e.g., that workspace_id and database_id must be obtained from list_workspaces/list_databases first). No mention of error handling for invalid IDs.
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 provided, so description must carry full burden. It fails to disclose whether this invalidates the old token, what error conditions to expect, or the format of the response (new token pair vs. access token only).
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?
Extremely brief single sentence with no redundancy. However, the brevity comes at the cost of necessary explanatory detail, making it under-specified rather than efficiently concise.
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 zero schema descriptions, no annotations, and no output schema, the description should explain the token flow, parameter details, and return values. It provides none of this, leaving critical gaps for proper agent operation.
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?
With 0% schema description coverage, the description inadequately compensates. While it mentions 'refresh token,' it does not describe the parameter's format, source (from login response), or the required 'request' wrapper object structure.
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?
States the specific action (refresh) and target (access token) but is somewhat tautological ('using refresh token'). Does not distinguish from sibling tool 'appflowy_login' or clarify the OAuth flow context.
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?
Provides no guidance on when to use this tool (e.g., when access token expires) versus the login tool, nor does it mention prerequisites like obtaining the refresh token from a previous authentication.
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 omits critical behavioral details: how row identity is determined for updates (no row_id in schema), whether updates are partial or full replacements, concurrency handling for pre_hash, and what constitutes existence checking.
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 single sentence wastes no words, but extreme brevity becomes under-specification. No front-loaded constraints or critical warnings about the identification mechanism that would prevent misuse.
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?
Inadequate for a complex mutation operation with nested objects and zero schema documentation. Missing: row identification logic, return value description, error conditions (e.g., conflicts), and field update semantics. The gap regarding how the tool identifies 'existing' rows is particularly critical.
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?
Schema coverage is 0% and the description fails to compensate. No explanation of the 'pre_hash' parameter (likely for optimistic locking), the structure expected within 'cells', the distinction between 'document' and 'cells', or how the target row is identified without a row_id parameter.
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 defines the upsert pattern (update or create) and identifies the resource (row). However, it fails to explicitly distinguish when to use this versus the sibling 'appflowy_create_row' tool, leaving ambiguity about selection criteria despite the functional overlap.
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 provided on when to prefer this tool over 'appflowy_create_row' or other alternatives. No mention of prerequisites, idempotency guarantees, or preconditions for the update path versus create path.
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 discloses nothing about safety (is it read-only?), side effects, rate limits, or return format. The word 'List' implies read-only, but this is not explicit.
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 single sentence is efficiently worded with no redundancy, but given the lack of annotations and schema coverage, this brevity results in under-specification rather than excellent conciseness.
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?
With no output schema, no annotations, and zero parameter documentation in the schema, the description fails to provide necessary context. It should at minimum describe the return structure (list of databases) and parameter semantics.
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 has 0% description coverage. While the description mentions 'workspace' implying the workspace_id parameter, it doesn't explain what a workspace_id is, where to obtain it (likely from appflowy_list_workspaces), or its format. Insufficient compensation for the schema deficiency.
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 uses a specific verb ('List') with clear resource ('databases') and scope ('in a workspace'). While it doesn't explicitly differentiate from siblings like appflowy_list_workspaces, the resource distinction is obvious from the tool names.
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 like appflowy_list_workspaces or how it relates to appflowy_get_database_fields. No mention of prerequisites or workflow context (e.g., that you typically need workspace_id from list_workspaces first).
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 fails to mention whether results are paginated, the format of returned row IDs, error conditions, or confirmation that this is a read-only operation (though implied by 'List').
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?
Extremely concise single sentence with no redundancy. However, it may be overly terse given the lack of supporting metadata (annotations/output schema), leaving significant informational gaps that could have been addressed with additional structured sentences.
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 0% schema coverage, no output schema, and no annotations, the description is insufficient. It omits parameter semantics, return value structure, and behavioral constraints that are necessary for correct invocation when structured metadata is absent.
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?
With 0% schema description coverage for the two required parameters, the description must compensate but fails to mention 'workspace_id' or 'database_id' at all. While the parameter names are somewhat self-descriptive, the description adds no semantic context about valid formats or where to obtain these values.
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?
States a specific verb (List) and resource (row IDs in a database), clearly distinguishing from sibling 'get_row_details' by specifying it returns only IDs rather than full details. However, it doesn't explicitly differentiate from 'list_databases' or 'list_workspaces' beyond the resource name.
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?
Provides no guidance on when to use this tool versus alternatives like 'get_row_details' or the prerequisite workflow (e.g., obtaining workspace_id/database_id from list_workspaces/list_databases). No 'when-not-to-use' or conditions are specified.
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 of behavioral disclosure. It compensates partially by describing the return values (access and refresh tokens) since no output schema exists, but it omits critical security context (handling passwords), error scenarios (invalid credentials), and token expiration behavior.
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 consists of two efficient sentences that are front-loaded with the most critical information (action and return values). Every sentence earns its place, though the extreme brevity contributes to gaps in other dimensions like parameter documentation.
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?
For an authentication tool with zero schema descriptions and no output schema, the description is insufficient. It omits security warnings for password handling, workflow context (relationship to refresh_token), and fails to document the required credentials parameters that the schema leaves undescribed.
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?
With 0% schema description coverage, the description must explain the parameters, but it fails entirely. It does not mention that 'email' and 'password' are required within the 'request' object, leaving the agent to infer this solely from the naked schema structure without semantic context.
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 ('Login to AppFlowy Cloud') and the specific outputs ('access token and refresh token'). It implicitly distinguishes itself from the sibling 'appflowy_refresh_token' by specifying that it returns both tokens, suggesting this is the initial acquisition method.
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?
There is no explicit guidance on when to use this tool versus the sibling 'appflowy_refresh_token', nor does it state that this should be invoked before other tools that require authentication. It lacks prerequisites (e.g., valid credentials must exist) and exclusion criteria.
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 disclosure burden. It adds important auth context ('authenticated user') given login/refresh siblings exist, implying prior authentication is required. However, it omits other behavioral details like pagination, caching, read-only safety confirmation, or return structure.
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?
Single sentence with zero waste. Information is front-loaded with the action verb, and 'for the authenticated user' efficiently establishes the security context without verbosity.
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 zero parameters and simple list semantics, the description is appropriately complete. However, without an output schema, it could have briefly characterized the return value (e.g., 'returns workspace IDs and names') to fully prepare the agent for invocation.
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?
Input schema has zero parameters, establishing a baseline of 4. The description appropriately does not introduce phantom parameters and the 'authenticated user' clause provides necessary context for the implicit auth token requirement.
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?
Description uses specific verb 'List' with clear resource 'workspaces' and scope 'for the authenticated user'. It effectively distinguishes from siblings like list_databases and list_rows by specifying the workspace resource level.
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?
While the description establishes the tool lists user-scoped workspaces, it lacks explicit guidance on when to use this versus list_databases or hierarchical navigation patterns. The usage is implied by the resource name but not stated explicitly.
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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