Alex Polonsky Profile
Server Details
Public, read-only professional profile and current availability for Alex Polonsky.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
2 toolsget_availabilityAlex Polonsky - AvailabilityARead-onlyInspect
Get Alex Polonsky's current public opportunity status, preferred work and engagement contexts, and public contact routes. Preserve the structure: primary_focus is the main focus; other_paid_engagements are selected paid options; co-building or founding requires a clear commercial or ownership arrangement. Include relevant professional_directions, location_preferences, work_modes, and contact_routes. Treat last_updated as the freshness indicator.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| status | Yes | |
| work_modes | Yes | |
| role_shapes | Yes | |
| last_updated | Yes | |
| canonical_url | Yes | |
| primary_focus | Yes | |
| contact_routes | Yes | |
| schema_version | Yes | |
| market_contexts | Yes | |
| company_contexts | Yes | |
| availability_version | Yes | |
| location_preferences | Yes | |
| other_paid_engagements | Yes | |
| professional_directions | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description consistently describes a read operation. It adds useful behavioral context beyond the annotation by defining field semantics, requiring preservation of structure, and identifying last_updated as the freshness indicator.
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 front-loaded with the core purpose, then adds meaningful field and freshness semantics. Some statements, such as 'primary_focus is the main focus,' are mildly tautological, but most sentences add value and the structure is organized.
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 there is an output schema, no parameters, and a read-only annotation, the description provides sufficient operational detail: field semantics, what to include, and how to interpret last_updated. It is slightly incomplete only in not addressing the relationship to get_profile.
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 tool has zero parameters and the schema coverage is 100%, so there is no parameter burden for the description to carry. The description reasonably focuses on output behavior rather than parameters.
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 opens with a specific verb and resource: 'Get Alex Polonsky's current public opportunity status, preferred work and engagement contexts, and public contact routes.' This clearly distinguishes availability from the sibling get_profile tool, even without naming it.
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 this tool is for querying current availability status, but it gives no explicit when-to-use or when-not-to-use guidance. It never mentions get_profile as an alternative or explains how to choose between the two tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_profileAlex Polonsky - Professional ProfileARead-onlyInspect
Get Alex Polonsky's curated public professional profile, including selected experience, demonstrated capabilities, journalism background, public projects, and future professional directions. This is selected evidence, not a complete CV. When summarizing examples, preserve their ownership qualifier exactly: led, owned_key_aspects, or contributed. Do not infer stronger ownership. If a list mixes things Alex built with work he contributed to or helped bring to market, frame it as built or contributed to, not built. Keep the action verbs and limits from contribution; do not reduce a contribution to an artifact name. Separate demonstrated experience from future directions. Use get_availability for current opportunity status.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| name | Yes | |
| summary | Yes | |
| headline | Yes | |
| location | Yes | |
| capabilities | Yes | |
| last_updated | Yes | |
| public_links | Yes | |
| canonical_url | Yes | |
| schema_version | Yes | |
| profile_version | Yes | |
| public_projects | Yes | |
| experience_scope | Yes | |
| future_directions | Yes | |
| selected_experience | Yes | |
| journalism_background | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description discloses important behavioral requirements: it warns against inferring stronger ownership, instructs exact preservation of qualifiers like led, owned_key_aspects, or contributed, and tells the agent to separate demonstrated experience from future directions. This goes well beyond the structured annotations and meaningfully shapes agent behavior.
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 front-loaded with the core purpose, then provides a concise caveat, followed by tightly worded summarization rules and a sibling-tool pointer. Every sentence carries meaningful guidance without repetition or filler, so the length is justified.
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 that there are no parameters and an output schema exists, the description covers everything an agent needs: what the profile contains, how to handle ownership qualifiers, how to treat mixed lists, how to separate experience from future directions, and where to look for current availability. No critical context is missing.
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 zero parameters, so there is nothing parameter-specific for the description to explain. Schema description coverage is 100%, and with zero parameters the baseline is 4; the description adds no parameter semantics because none are needed.
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 starts with a specific verb and resource: 'Get Alex Polonsky's curated public professional profile,' then enumerates content areas such as selected experience, demonstrated capabilities, journalism background, public projects, and future directions. It also distinguishes itself from the sibling tool by pointing to get_availability for current opportunity status, so an agent can easily tell them apart.
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 explicitly routes the agent to the sibling tool: 'Use get_availability for current opportunity status.' It also sets expectations about the data being selected evidence rather than a complete CV, giving clear context on when this tool is appropriate and what it should not be used as.
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
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.
Discussions
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
get_availability and get_profile have clearly distinct purposes: one covers current opportunity status and contact routes, the other covers professional background and demonstrated experience. The slight overlap in mentioning professional directions is minor and both descriptions direct agents to the correct tool.
Both tools follow a consistent get_<resource> convention, making the pattern predictable and easy to extend. There are no mixed naming styles or vague verbs.
Two tools is slightly thin for a general profile server, but the narrow scope of exposing a curated public profile plus current availability makes the count reasonable. Each tool earns its place without unnecessary fragmentation.
For a read-only public profile server, the pair covers the two essential surfaces: background information and current availability. There are no obvious dead ends or missing operations that would cause agent failures in the intended use case.