AWS cloud security scanners for AI agents — S3, IAM, EC2, EKS, RDS, CloudTrail, CloudWatch Logs
Get full metadata, SHA256 hash, download URL, and ready-to-run shell command for a Kloudle scanner binary. Pass args to get a complete command; omit for a template with placeholders.
| Name | Required | Description | Default |
|---|---|---|---|
| args | No | CLI args as key-value pairs (e.g., {'region': 'us-east-1'}) | |
| name | Yes | Binary name (e.g., 'k5e-aws-s3') |
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 does disclose useful behavioral traits, such as the effect of args on the generated command and the return items (metadata, hash, URL, command). However, it does not explicitly state that the operation is read-only or mention any authentication or rate limit considerations, relying on the word 'Get' to imply safety.
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 concise sentences that front-load the primary purpose and then add the key nuance about args. No words are wasted, and the structure is easy to scan.
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 two parameters and no output schema, the description covers the essential information: what the tool returns (metadata, hash, URL, shell command) and how args modify the command. It does not address potential errors or prerequisites, but for this complexity level, the coverage is 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?
The schema already describes both parameters with 100% coverage, so the baseline is 3. The description adds meaningful context by explaining how the 'args' parameter affects the output ('complete command' vs 'template with placeholders'), which goes beyond the schema's simple 'CLI args as key-value pairs' description.
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 specifies the tool's function: 'Get full metadata, SHA256 hash, download URL, and ready-to-run shell command for a Kloudle scanner binary.' This distinguishes it from the sibling tool 'search', which likely finds binaries, whereas 'get' retrieves details for a specific binary.
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 provides some usage guidance by explaining that passing args yields a complete command while omitting them produces a template, but it does not explicitly mention when to use this tool versus the sibling 'search' tool. The context implies you would use 'get' after finding a binary with 'search', but this is not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find Kloudle cloud security scanners by capability. Returns matching binaries with name, description, check count, and severity breakdown.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query (e.g., 's3 encryption', 'iam', 'public access') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool returns matching binaries with specific fields (name, description, check count, severity breakdown), which is useful. However, it does not mention potential limitations like pagination, empty results, or any permissions required.
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, front-loaded with the tool's purpose followed by the return format. Every word earns its place, with no redundancy or irrelevant detail.
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 single-parameter search tool with no output schema, the description is complete: it states what the tool does, what it returns, and the schema covers the input. Since there is no output schema, the return description is necessary and provided.
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?
The input schema has 100% coverage with a description of the 'query' parameter including examples. The tool description adds the phrase 'by capability', which clarifies the meaning of the query parameter, but this is only a minor addition over the 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 uses a specific verb ('Find') and resource ('Kloudle cloud security scanners') with the search criterion 'by capability'. This clearly differentiates it from the sibling tool 'get', which presumably retrieves a specific item.
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 clearly states the tool is for finding scanners by capability, which gives context for when to use it. It does not explicitly mention alternatives or exclusions, but the context is clear enough to imply the appropriate use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
getsearchClaiming 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, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on 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
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
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
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Pay-per-call cybersecurity for AI agents: vuln scans, threat intel, compliance, code security.
Threat modeling, code/cloud/pipeline scanning, shadow-AI discovery, compliance checks and fixes.
Zero-config MCP security scanner for AI-generated apps. 25K+ vulnerability patterns.
HIPAA compliance AI agent — scan, grade, SRA, and generate compliance docs.
Add one secure layer between your agents and this server.
The two tools, 'get' and 'search', serve clearly distinct purposes: 'search' finds scanners by capability, while 'get' retrieves detailed metadata for a specific scanner. There is no functional overlap or ambiguity between them.
Both tool names are single-word imperative verbs ('get', 'search'), following a consistent and predictable naming style. The pattern is simple and easy for an agent to recognize.
With only two tools, the server feels thin for a 'Cloud Security Scanner' platform, but the scope is narrowly focused on binary discovery and retrieval. It is borderline, not excessive, and could benefit from additional tools for broader scanner management.
The tool set covers the core workflow: 'search' for discovery and 'get' for obtaining full metadata, hashes, download URLs, and ready-to-run commands. There are no obvious dead ends or missing operations for the stated purpose of accessing Kloudle scanner binaries.
