Blocksize Market Data

Overview Schema Related Servers Score Discussions

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation4/5
Each tool has a distinct purpose, but 'search' and 'fetch' both deal with catalog entries, and 'list_instruments' and 'search_pairs' both involve instruments, leading to possible confusion.
Naming Consistency4/5
Most tools follow a verb_noun pattern, but 'fetch' lacks an underscore, and the verbs vary between 'get_', 'list_', 'search_', and 'fetch', introducing minor inconsistency.
Tool Count5/5
Seven tools is an appropriate number for a market data server, covering catalog inspection, search, pricing, and endpoint building without being excessive.
Completeness3/5
The set covers catalog, search, and pricing, but lacks tools for actual market data retrieval (only endpoint building is provided) and direct instrument data querying, leaving notable gaps.
Average 3.7/5 across 7 of 7 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
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.
View related servers

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?
With no annotations, the description should disclose behavioral traits like read-only status, authentication needs, or response size. It only lists contents without explaining side effects or data freshness, leaving significant gaps for the agent.
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 sentence listing key items, which is reasonably concise. It could be slightly better structured (e.g., separate sentence for upgrade path), but it efficiently conveys the tool's purpose without filler.
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 zero parameters and the presence of an output schema, the description adequately lists what the tool returns. However, it lacks completeness by not specifying that it is a read-only listing or clarifying how the output relates to sibling tools like get_pricing_info.
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 schema coverage is trivially 100%. The description adds value by explaining what the output includes (products, credits, endpoints, upgrade path), compensating for the lack of parameters and providing context beyond the schema.
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 identifies the tool as inspecting the product catalog of Blocksize raw data and premium workflow products, listing specific items like credits and upgrade paths. It distinguishes from siblings like get_pricing_info and list_instruments by focusing on the catalog overview.
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 guidance on when to use this tool versus siblings, such as get_pricing_info for pricing details or get_market_data_endpoint for endpoint specifics. No explicit when-to-use or when-not-to-use context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It adds 'Free and read-only,' which is helpful but lacks details on rate limits, pagination, or response characteristics. The output schema exists but doesn't compensate for the lack of behavioral context in the description itself.
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—one sentence with no wasted words. For a simple tool with one parameter, this is appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one param, output schema exists), the description covers the basics but remains vague about query syntax and result handling. It is minimally viable but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'query,' so the schema already provides meaning. The description does not add any additional semantics beyond what the schema states.
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 tool's purpose is clearly stated: 'Search Blocksize docs/catalog entries.' The verb 'search' and the resource 'Blocksize docs/catalog entries' are specific, though 'catalog entries' is slightly vague. It distinguishes from the sibling 'search_pairs' by context, but not explicitly.
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 only 'Free and read-only,' which implies safe usage but offers no guidance on when to use this tool versus siblings like 'fetch' or 'search_pairs.' No alternatives or exclusions are given.
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 states 'read-only' which implies no destructive effects, and 'free' suggests no cost. However, it does not disclose behaviors like rate limits, error handling, or pagination, though for a simple list tool this is acceptable.
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, consisting of two short sentences with no superfluous information. Every word is purposeful.
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 tool is simple with one optional parameter and an output schema exists, so return values need not be explained. The description covers the primary function, but could mention the default value of 'service' and behavior for invalid inputs for complete clarity.
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% for the single parameter 'service', which has a clear description in the schema. The tool description adds no additional meaning beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'supported instruments' with scope 'for one Blocksize service.' It adds 'Free and read-only' for extra clarity. However, it does not explicitly differentiate from sibling tools like 'search_pairs' which might also list instruments.
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 omits any context about selection criteria or exclusions, leaving the agent without decision support.
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?
The description discloses that the tool is free and read-only, and does not fetch live prices. These are important behavioral traits, especially since no annotations are provided. However, it could mention that results are based on a search query, but overall it is sufficiently transparent.
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 concise at 12 words, front-loading the action. It could be slightly more structured, but it contains no filler and every phrase 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?
Given the 100% schema coverage and existence of an output schema, the description adequately covers basic behavior. However, it lacks guidance on how to differentiate among sibling tools (e.g., search vs. list_instruments) and does not mention search behavior like fuzzy matching.
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%: both parameters (query and asset_class) have clear descriptions. The tool description adds no further meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
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 'Search supported Blocksize instruments,' specifying the verb and resource. It adds 'Free, read-only, and does not fetch live prices,' which distinguishes it from sibling data-fetching tools like get_pricing_info or get_market_data_endpoint.
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 implicitly indicates read-only use for discovery, but it does not explicitly state when to use this tool over siblings like 'search' or 'list_instruments.' No specific when-not-to-use or alternative guidance 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?
No annotations are provided, so the description bears full burden. It discloses a key behavior: the tool does not start a payment. However, it omits other important traits such as authentication requirements, rate limits, or whether it caches data. Adds some value but could be more comprehensive.
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 with no unnecessary words. It is front-loaded and efficient, earning its place without 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?
An output schema exists (not shown but noted), so the description does not need to detail return structure. It covers the high-level content—pricing, starter-credit positioning, settlement guidance. Could benefit from briefly explaining what 'settlement guidance' entails, but overall it is sufficient for a parameterless info tool.
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 zero parameters, and schema description coverage is 100% (vacuously). The description does not need to add parameter meaning. With no parameters, a baseline score of 4 is appropriate; the description provides adequate context for what the tool returns.
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 'Return' and clearly identifies the resources: Blocksize pricing, starter-credit positioning, and settlement guidance. It distinguishes itself from sibling tools like get_product_catalog or get_market_data_endpoint by noting 'without starting payment,' implying this is an information-only endpoint.
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 phrase 'without starting payment' suggests this tool is for previewing pricing and guidance before initiating a payment, but there is no explicit comparison to sibling tools or mention of when not to use this tool. Adequate but lacks clear exclusion criteria.
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, description carries full burden. It clearly states no side effects: does not call endpoint or initiate payment. This is sufficient for a non-destructive URL builder tool.
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 of 11 words, front-loaded with action verb. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists to document return structure. Description sufficiently defines purpose and non-side-effect behavior for a low-complexity tool with 2 parameters.
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 100% with clear descriptions for both parameters. Description adds no extra parameter information, so baseline score of 3 is appropriate.
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 'Build' and resource 'paid x402 HTTP endpoint URL', clearly distinguishing from sibling tools like 'fetch' which would call the endpoint. Scope is explicit: builds URL without executing or starting payment.
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?
Implies use case: preparing a URL before fetching. But lacks explicit guidance on when to use this vs siblings (e.g., fetch, get_pricing_info). No exclusions or alternatives mentioned.
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?
No annotations provided, so description carries full burden. It discloses that the tool is free and read-only, which are important behavioral traits. It does not cover error handling or rate limits, but for a simple fetch, this may suffice.
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 short sentences with no fluff. Every word serves a purpose. Front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema present), the description covers purpose, usage context, and safety. No missing information required for a fetch tool.
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 100%, and the schema already describes the 'id' parameter as 'Result id returned by search.' The description repeats this exactly, adding no new meaning. Baseline 3 is appropriate.
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 fetches one docs/catalog entry returned by search. It distinguishes from sibling tools like 'search' (which returns many) and 'get_product_catalog' (which might return all). Verb 'Fetch' with resource 'docs/catalog entry' is specific.
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 usage after search, as it says 'returned by search'. It also notes 'Free and read-only,' indicating safe usage. However, it does not explicitly state when not to use it or mention alternatives beyond the sibling list.
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

blocksize-agentic-payments-mcp MCP server

Copy to your README.md:

[![blocksize-agentic-payments-mcp MCP server](https://glama.ai/mcp/servers/jf-cmyk/blocksize-agentic-payments-mcp/badges/card.svg)](https://glama.ai/mcp/servers/jf-cmyk/blocksize-agentic-payments-mcp)

Score Badge

Copy to your README.md:

[![blocksize-agentic-payments-mcp MCP server](https://glama.ai/mcp/servers/jf-cmyk/blocksize-agentic-payments-mcp/badges/score.svg)](https://glama.ai/mcp/servers/jf-cmyk/blocksize-agentic-payments-mcp)

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/jf-cmyk/blocksize-agentic-payments-mcp'

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