Quote Collection MCP-Server

by edkeric

Overview Schema Related Servers Score Discussions

JavaScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: adding, importing, searching, random selection, deletion, and listing. No two tools overlap in functionality; search and random both filter but serve different intents (finding specific vs. retrieving a random quote).
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_caseadd_quote, import_quotes, search_quotes, random_quote, delete_quote, list_quotes). The pattern is uniform and predictable.
Tool Count5/5
Six tools is well within the ideal 3-15 range for a focused domain like a quote collection. Each tool serves a necessary function without redundancy or bloat.
Completeness4/5
The set covers create (add, import), read (list, search, random), and delete, but lacks an update operation for editing existing quotes. This is a minor gap since quotes are typically static, but an update tool would complete the CRUD lifecycle.
Average 3.7/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues 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 status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 the full burden of behavioral disclosure. It explicitly says the action is 'Delete', which conveys destruction, but it does not disclose permanence, irreversibility, required permissions, or any cascading effects. For a destructive operation, this is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise, front-loaded sentence with zero wasted words. It clearly states the action, the target resource, and the required identifier.
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?
With one required parameter, 100% schema coverage, and no nested objects, the description is mostly sufficient for basic invocation. However, because there are no annotations, the destructive nature, irreversibility, and any danger implications are left to the agent to infer, making the context incomplete for risk-aware tool 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%, and the schema already fully describes 'id' as the unique ID of the quote to delete. The description repeats nearly the same wording and adds no additional semantic detail beyond what the schema provides, so the baseline 3 applies.
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 is a specific verb+resource statement: 'Delete a quote' by its unique ID. It is clearly distinguishable from all sibling tools (add, import, list, random, search) since it uniquely describes a destructive deletion operation.
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 gives no guidance on when to use this tool versus alternatives, no prerequisites, and no mention of needing to find the ID first (e.g., via search_quotes or list_quotes). The only implied condition is that the caller must know the quote's unique ID.
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 is the sole source of behavioral information. While 'Get' implies read-only, the description does not disclose side effects, randomness guarantees, return format, or any rate limits. It remains minimal and does not go beyond the basic function.
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 sentence that begins with the core action 'Get a random quote' and then adds the optional filtering. It is concise, well-structured, and free of redundant detail.
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?
For a tool with three optional parameters and no output schema, the description is reasonably complete but lacks key context such as the return type (single quote vs. array), any pagination, or behavior when no filter matches. Given the absence of an output schema, the description should specify the response shape, which it does not.
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 input schema already provides descriptions for each parameter (100% coverage), and the description repeats that they are optional filters. It adds little beyond the schema, so the baseline of 3 is appropriate. No additional meaning is provided about value formats or constraints.
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 retrieves a random quote, with optional filters. The verb 'Get' and resource 'random quote' are specific, and the mention of filtering distinguishes it from simple retrieval tools like list_quotes or deletion tools like delete_quote.
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 does not provide any guidance on when to use this tool versus alternatives. It does not mention when to prefer this over search_quotes or list_quotes, nor does it indicate exclusivity or prerequisites. The agent is left to infer appropriateness from the name and sibling names.
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 bears the full burden of explaining behavior. It only says 'Import multiple quotes at once' and does not disclose whether duplicates are handled, whether existing quotes are replaced, what validations occur, or what the operation returns. For a mutation/creation tool, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient, front-loaded sentence with no filler or repetition. Every phrase earns its place, and the core action is clear from the start.
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?
The tool inputs are simple, but no annotations, no output schema, and no behavior details mean the description alone does not fully prepare an agent. Missing context includes how duplicates are handled, whether an import is atomic, any validation rules, and what a successful import returns. This is below the minimum viable bar for a batched create operation.
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 already documents the quotes parameter as 'Array of quotes to import,' so the description adds no further parameter meaning. The nested required fields (text, author_tag, topic_tag, language_tag) have no individual descriptions, and the tool description does not clarify their semantics either, relying on their self-explanatory names.
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 a specific action ('Import') and resource ('multiple quotes at once'), which distinguishes it from its sibling add_quote by emphasizing batch operation. Even without naming the sibling, the purpose is obvious and unambiguous.
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 'multiple quotes at once' clearly signals that this tool is for batch imports rather than single additions, which is a clear usage context. However, it does not explicitly name alternatives like add_quote or mention when not to use it, so it stops short of a 5.
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 must carry the behavioral burden. It discloses the matching logic (case-insensitive substring) and that the search spans quote text and tags, which is helpful. However, it does not explicitly state that the operation is read-only (though obvious for a search) or describe the return structure/pagination, leaving some 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 two sentences, front-loaded with the core purpose and then the matching detail. Every word earns its place; no fluff or repetition of the schema.
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?
For a simple single-parameter search tool with no output schema and no nested objects, the description covers the essential aspects: search scope and matching semantics. It omits details like result ordering or pagination, but these are less critical for a search tool and can be reasonably inferred from the name and common expectations.
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 parameter schema provides a clear description (searches across quote text and all tags), achieving 100% schema coverage. The tool description adds extra semantics by specifying case-insensitive substring matching, which goes beyond the schema. This enriches the parameter understanding without redundancy.
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 a specific verb ('Search') and resource ('quotes'), and specifies the search dimensions (text, author/topic/language tags) and matching behavior (case-insensitive substring). However, it does not explicitly differentiate from siblings like list_quotes or random_quote, though the name and its search-centric wording imply the distinction.
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 implies when to use this tool (for targeted quote searching) but provides no explicit guidance on when not to use it or viable alternatives. Siblings like list_quotes or random_quote are not mentioned, leaving the agent to infer context 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It clearly states the core effect — adding a quote to the collection — but it does not disclose behavior around duplicates, tag validation, or what happens upon success.
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, front-loaded sentence with no filler. Every word is functional, and it avoids re-listing schema properties.
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?
For a simple add operation with fully described required parameters and no output schema, this is mostly complete. It could still mention duplicate behavior or a successful response, but the basic context is sufficient for an agent to invoke it 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 description coverage is 100%, and each parameter already has a meaningful description with examples. The tool description adds no additional parameter-level detail, so it sits at the schema-driven baseline.
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 names a specific verb and resource: 'Add' a 'single new quote'. The word 'single' clearly contrasts with the sibling import_quotes, and the collection context makes the target explicit. This is enough for an agent to select the tool confidently.
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 implies this is for adding one quote at a time, which differentiates it from import_quotes, but it does not explicitly state when to prefer this tool over alternatives. No exclusions or if-then routing guidance is provided.
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 unambiguously presents the operation as a non-mutating retrieval of all stored quotes, which is the key behavioral trait. It does not mention ordering or pagination, but for a zero-parameter list operation the description is sufficiently transparent about the operation's nature.
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?
A single, direct sentence with no redundant wording. It opens with the operation and immediately defines the scope. Every word contributes to the meaning.
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 zero-parameter surface, the description is nearly complete: an agent can safely invoke the tool without additional setup. It does not mention return shape or pagination, but for a simple list-all operation with no output schema, this is acceptable and low-risk.
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 no parameters, and the input schema is empty, so there is no parameter burden on the description. The description's mention of 'every quote' clarifies the retrieval scope, which adds slight semantic value beyond the schema, though not much is required.
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 operation: 'List every quote currently stored in the collection.' The verb is explicit, the resource is specific, and the scope ('every quote') distinguishes it from filtered or random retrieval tools like search_quotes and random_quote.
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 'every quote currently stored in the collection' gives clear context for when an agent should use this tool: when it needs the full collection. It does not explicitly compare against sibling tools or state when-not-to-use, but the scope is obvious enough to guide selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![mcp-quote-server MCP server](https://glama.ai/mcp/servers/edkeric/mcp-quote-server/badges/card.svg)](https://glama.ai/mcp/servers/edkeric/mcp-quote-server)

Score Badge

Copy to your README.md:

[![mcp-quote-server MCP server](https://glama.ai/mcp/servers/edkeric/mcp-quote-server/badges/score.svg)](https://glama.ai/mcp/servers/edkeric/mcp-quote-server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
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

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/edkeric/mcp-quote-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server