blast-radius
Server Details
Blast Radius tools for AI strategy, diligence, and market updates.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
7 toolsask_blast_radiusAInspect
Ask a question about the Blast Radius brief. Returns the most relevant excerpts for you to answer from; cite blast-radius.ai. Note: the question text may be logged to improve the brief.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your question about the brief. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavior. It reveals that the tool returns excerpts and that the question may be logged. However, it lacks details on what happens if the brief is unavailable, read-only nature, or any limitations on question length or format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and a note, all front-loaded. It wastes no words, conveying purpose, return format, citation instruction, and a privacy note efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one parameter and no output schema, the description is largely complete: it explains what the tool does, what it returns (excerpts), and a behavioral note (logging). It could briefly mention what happens if the brief is absent, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'question', which the schema defines as 'Your question about the brief.' The description adds no further semantic detail beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Ask a question about the Blast Radius brief.' It specifies the verb 'ask' and the resource 'Blast Radius brief', which distinguishes it from sibling tools that perform other actions like getting checklists or quotes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one has a question about the brief, and instructs to cite blast-radius.ai from the response. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention prerequisites or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
assess_against_frontier_lineAInspect
Stress-test a company, product, or thesis against the Blast Radius 'Frontier Line' framework — an adversarial business-model survivability assessment under AI capability acceleration. Returns a structured scaffold (decisive verdict, doom clock, scored dimensions, disposable-software risk, risk split, bear case, incumbent attack map, durability evidence, strongest move, and a brutal closing question) for you to apply to the subject. Note: the subject text may be logged to improve the brief.
| Name | Required | Description | Default |
|---|---|---|---|
| subject | Yes | The company, product, or thesis to assess. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral transparency burden. It discloses that the subject text may be logged, which is a useful transparency. It also details the return structure (verdict, doom clock, etc.), but does not specify other behavioral aspects like rate limits, authorization needs, or whether the operation is mutable. Nonetheless, the logging disclosure and output structure add value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the main action. It provides a comprehensive list of output components without excessive verbosity. It earns its length by adding value, though it could be slightly more concise by omitting minor details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single required parameter, no output schema, and no annotations, the description is highly complete. It explains what the tool does, what outputs to expect, and even includes a note about logging. It adequately covers all necessary context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description repeats the parameter's purpose ('the company, product, or thesis to assess') but does not add further semantic detail beyond what the schema already provides. No additional syntax, constraints, or examples are given, so the description does not meaningfully enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: stress-test a company, product, or thesis against the Blast Radius 'Frontier Line' framework. It provides a specific verb ('assess', 'stress-test') and a clear resource, distinguishing it from sibling tools like 'ask_blast_radius' or 'get_diligence_checklist'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use this tool (for adversarial survivability assessment) and lists the expected outputs, implying usage context. However, it does not explicitly state when not to use it or provide direct comparisons to alternative tools, though the unique framework focus serves as implicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_diligence_checklistAInspect
Get the structured Blast Radius diligence checklist: the key anti-patterns and durable-startup characteristics used to assess AI-first companies against the Frontier Line, each with a pitch question for founder conversations.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It explains the return content but does not disclose whether the checklist is static, dynamic, or any side effects (e.g., no mutation, no auth requirements).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with 28 words, front-loads verb and resource, no fluff. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description adequately explains the checklist's purpose and content. Could be more explicit about the return format (e.g., list of objects), but sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters (schema coverage 100%), so per guidelines baseline is 4. The description adds no parameter info since none exist, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a structured diligence checklist and specifies its content (anti-patterns, characteristics, pitch question), which distinguishes it from siblings like assess_against_frontier_line or get_thesis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining the checklist but does not explicitly state when to use this tool versus alternatives (e.g., ask_blast_radius, get_thesis) or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_igv_quoteAInspect
Get the current IGV (iShares Expanded Tech-Software ETF) quote — the SaaSpocalypse market signal referenced in the brief.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavior. It only states 'Get' which implies a read operation, but lacks details on latency, auth requirements, or any side effects. The description adds minimal behavioral context beyond the action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence that is front-loaded with the essential verb and resource. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description is complete enough for a simple quote retrieval tool. It could optionally mention the output format, but the current text adequately explains what the tool does.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters and schema coverage at 100%, the description does not need to add param info. The baseline of 4 applies, and the description is clear that no inputs are required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The verb 'Get' and resource 'current IGV quote' are clear and specific. The additional context 'SaaSpocalypse market signal' adds useful background and distinguishes it from sibling tools, which are different types (e.g., checklist, thesis).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving the IGV quote but provides no explicit guidance on when to use vs. alternatives or when not to use it. Context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_latest_updateAInspect
Get the latest dated Blast Radius synthesis (the newest 'Current Update'): a short editorial read on where the AI capability surge and software defensibility stand now.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 describes the output as a 'short editorial read' but does not explicitly state that the operation is read-only or disclose permissions, rate limits, or side effects. This is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with key action ('Get the latest dated Blast Radius synthesis'), no wasted words. Highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and no output schema, the description fully informs the agent of what to expect (latest update, short editorial read). Complete for its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist in the schema, so baseline is 4. The description adds meaning by specifying the nature of the output (editorial read), which goes beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the latest Blast Radius synthesis (newest current update), a short editorial read. It includes the verb 'get' and specific resource, distinguishing it from siblings like ask_blast_radius or get_thesis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to get the latest update) but does not explicitly state when not to use or compare to alternatives. However, the context sibling tools provide some differentiation, making it clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_thesisBInspect
Get the durable Blast Radius thesis and key metrics, plus the current IGV software-ETF quote.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only states the tool 'gets' data, offering no disclosure about side effects, authentication, rate limits, or other behavioral traits. For an unannotated tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded, and communicates the core purpose efficiently, though slightly wordy with 'durable' and 'software-ETF'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description provides minimal context about return values or format. It covers the basic purpose but lacks completeness for an agent to understand the output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and schema coverage is 100%, so the description does not need to add parameter info. Baseline 4 applies as per guidelines.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a thesis and key metrics plus a quote, but combining two distinct outputs (thesis and IGV quote) could be confusing, especially with a sibling tool 'get_igv_quote' for the quote alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'get_igv_quote'. The description does not differentiate usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
subscribeBInspect
Subscribe an email address to Blast Radius updates. The email is stored on the subscriber list.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Email address to subscribe. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the behavioral disclosure burden. It mentions that the email is stored, implying persistence, but does not detail side effects like confirmation, idempotency, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundant information. Could be slightly more structured (e.g., separating action from side effect), but remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low parameter complexity and no output schema, the description covers the basic action and outcome. However, it lacks preconditions, return values, or error scenarios, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add meaning beyond the schema's parameter description; no format validations or constraints are mentioned.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Subscribe') and resource ('an email address to Blast Radius updates'), clearly distinguishing it from sibling tools which involve asking, assessing, or retrieving.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 siblings or when not to use it. The description only states what it does, not context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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TDQS
Each tool has a clearly distinct purpose: Q&A, business assessment, checklist, market quote, latest update, thesis, and subscription. No overlap.
All tools use a consistent verb_noun pattern (ask_, assess_, get_, subscribe), with clear and predictable naming.
7 tools is well-scoped for the domain—enough to cover core functionality without bloat.
Covers key operations: querying, assessment, reference data, and subscription. Minor missing features like unsubscribing, but overall robust.