AINative ZeroDB MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but zerodb_search_memory and zerodb_search_vectors could be confusing as both involve semantic similarity searches. The descriptions clarify that one searches 'agent memory' and the other searches 'vectors', but the overlap in functionality might cause misselection without careful reading.
Naming Consistency5/5
All tools follow a consistent zerodb_verb_noun naming pattern with snake_case throughout. The verbs (get, renew, search, store) are clear and predictable, making the tool set easy to navigate and understand at a glance.
Tool Count5/5
With 6 tools, this server is well-scoped for managing agent context and memory in ZeroDB. Each tool serves a specific function (e.g., authentication, storage, retrieval), and there are no redundant or trivial tools, making the count appropriate for the domain.
Completeness4/5
The tool set covers core operations for agent context and memory management, including get, renew, search, and store functions. A minor gap exists in update or delete operations for stored memories or vectors, which agents might need for lifecycle management, but the current tools support basic workflows effectively.
Average 2.9/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 4 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool searches vectors semantically but doesn't cover critical aspects like whether it's read-only, if it requires authentication, rate limits, error handling, or what the output looks like. This is inadequate for a search tool with no annotation support.
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 no wasted words. It's front-loaded with the core purpose and appropriately sized for the tool's complexity, making it easy to parse quickly.
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's complexity (semantic search with vector inputs), lack of annotations, and no output schema, the description is insufficient. It doesn't explain the return format, error cases, or behavioral traits, leaving significant gaps for the agent to operate effectively.
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 clear descriptions for all parameters (e.g., 'Query vector (exactly 1536 dimensions required)'). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 without compensating or detracting.
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 vectors using semantic similarity' clearly states the action (search) and resource (vectors) with a method (semantic similarity), but it doesn't distinguish this tool from its sibling 'zerodb_search_memory'. Both involve searching, so the purpose is clear but lacks 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?
The description provides no guidance on when to use this tool versus alternatives like 'zerodb_search_memory' or other siblings. There's no mention of prerequisites, context, or exclusions, leaving the agent with no usage direction beyond the basic purpose.
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 the full burden but only states the basic action. It doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (e.g., structured data or raw text), leaving significant 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, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose without unnecessary elaboration, earning full marks for brevity and structure.
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's complexity (retrieving context with parameters) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects, output details, or usage context, failing to compensate for the missing structured information.
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 has 100% coverage, fully describing the three parameters (agent_id, max_tokens, session_id). The description adds no additional meaning beyond the schema, such as explaining how parameters interact or default behaviors, so it meets the baseline but doesn't 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 action ('Get') and resource ('agent context window for current session'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'zerodb_search_memory' or 'zerodb_search_vectors' that might also retrieve context-related data, missing explicit distinction.
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. The description implies it's for retrieving context in a session, but it doesn't specify prerequisites, exclusions, or compare to siblings like 'zerodb_search_memory' for broader searches, leaving usage unclear.
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 the tool 'renews' a token, implying a mutation that likely requires authentication or specific permissions, but doesn't clarify if this is a safe operation, what side effects occur (e.g., invalidating old tokens), or any rate limits. The description adds minimal behavioral context beyond the basic action.
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 ('Manually renew authentication token') that directly states the tool's purpose without any fluff or redundancy. It's front-loaded and wastes no words, making it highly concise and well-structured for quick understanding.
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 complexity of authentication token renewal (a mutation with potential side effects), the description is incomplete. With no annotations and no output schema, it fails to explain critical aspects like what the renewed token looks like, any prerequisites, error conditions, or how it integrates with sibling tools. This leaves significant gaps for an agent to use the tool effectively.
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 tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately avoids mentioning any. This meets the baseline for tools with no parameters, as it doesn't mislead or omit necessary details.
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 'Manually renew authentication token' states a clear action ('renew') on a specific resource ('authentication token'), which meets the basic requirement. However, it doesn't differentiate this from sibling tools like 'zerodb_get_context' or 'zerodb_search_memory', nor does it specify what system or context this token belongs to, leaving some ambiguity about scope.
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., when tokens expire), conditions for use, or how it relates to sibling tools like 'zerodb_get_context' (which might retrieve token info). This lack of context makes it unclear when an agent should invoke this tool.
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 'Search' implies a read-only operation, it doesn't specify whether this is a simple lookup or a more complex semantic search, what the response format looks like, or any performance characteristics like latency or result ordering. The mention of 'semantic similarity' is helpful but insufficient for full 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 that gets straight to the point without any wasted words. It's appropriately sized for a search tool and front-loads the core functionality effectively.
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 a search tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what constitutes 'agent memory', how results are returned, what 'semantic similarity' means in practice, or how this differs from sibling tools. The agent would need to guess about important behavioral aspects.
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 5 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining how the 'query' parameter interacts with 'semantic similarity' or clarifying the relationships between filtering parameters. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search') and resource ('agent memory') with the method ('using semantic similarity'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'zerodb_search_vectors' or 'zerodb_get_context', which likely have overlapping search functionality.
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. With siblings like 'zerodb_search_vectors' and 'zerodb_get_context' available, there's no indication of what makes this tool distinct or when it should be preferred over other search or retrieval 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?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits such as whether this is a write operation (implied by 'store'), potential side effects, authentication needs, rate limits, or how it handles auto-generated IDs. This leaves significant gaps for a tool that modifies persistent storage.
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. Every word earns its place with no redundancy or unnecessary elaboration, making it highly concise and well-structured.
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 complexity of a storage tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects, error handling, return values, and how it integrates with sibling tools, leaving the agent with insufficient context for reliable use.
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 all 5 parameters. The description adds no additional parameter semantics beyond implying 'content' and 'role' are core inputs. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't compensate with extra 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 ('Store') and resource ('agent memory in ZeroDB') with the purpose of 'persistent context'. It distinguishes from sibling tools like 'zerodb_get_context' (retrieval) and 'zerodb_store_vector' (vector storage), but doesn't explicitly contrast with 'zerodb_search_memory' which might overlap in purpose.
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 explicit guidance on when to use this tool versus alternatives like 'zerodb_search_memory' or 'zerodb_store_vector'. The description implies usage for storing memory content, but lacks context about prerequisites, when not to use it, or comparisons with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the dimensionality requirement ('exactly 1536 dimensions'), which is a constraint, but fails to cover other critical aspects like authentication needs, rate limits, idempotency, or what happens on success/failure. For a storage tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 function and key constraint. It is front-loaded with the core purpose and avoids unnecessary details, making it highly concise and well-structured without any wasted words.
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 complexity of a storage operation with no annotations and no output schema, the description is insufficient. It lacks information on return values, error handling, side effects, and how it integrates with sibling tools. For a tool that modifies data (implied by 'Store'), more context is needed to ensure safe and effective use by an AI agent.
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 by reiterating the dimensionality constraint for 'vector_embedding', which is also covered in the schema via minItems/maxItems. No additional semantic context is provided beyond what the schema offers, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Store') and resource ('vector embedding with metadata'), making the purpose evident. However, it does not explicitly differentiate this tool from sibling tools like 'zerodb_store_memory', which might have similar storage functions but for different data types, leaving some ambiguity in sibling distinction.
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, such as 'zerodb_store_memory' or other storage-related siblings. It lacks context on prerequisites, exclusions, or specific scenarios for application, offering only a basic functional statement without usage context.
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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