StackFiesta
Server Details
Discover AI tools for game development — 100+ tools indexed by engine, task, and pricing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.6/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: find_tools searches for tools with filters, while get_tool retrieves details of a specific tool. No overlap.
Both tools follow a consistent verb_noun pattern: find_tools and get_tool. Naming is predictable and clear.
With only 2 tools, the surface is minimal but sufficient for basic catalog browsing. However, it may feel thin for a full-featured API.
The set covers search and detail retrieval, which are core operations for a catalog. However, missing operations like listing categories or browsing by other criteria leave minor gaps.
Available Tools
2 toolsfind_toolsAInspect
Search AI tools for game development from the StackFiesta catalog. Supports filtering by engine, pricing, type, and category. Returns paginated results (max 24).
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filter by tool type: mcp-server, plugin, skill, prompt, api | |
| limit | No | Maximum results (default 10, max 24) | |
| query | Yes | Search query (full-text search) | |
| engine | No | Filter by game engine: unity, unreal, godot, bevy, etc. | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." | |
| pricing | No | Filter by pricing model: free, freemium, paid, open-source | |
| category | No | Filter by category slug (e.g. ai-coding, level-design, npc-ai) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses pagination (max 24 results) but does not mention authorization needs, rate limits, or behavior on empty results. Minimal disclosure beyond basic functionality.
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, front-loaded with purpose, no unnecessary words. Efficient and to the point.
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 7 parameters, 2 required, and no output schema, the description is adequate but could mention return format or fields. It specifies pagination but lacks details on query behavior. Slightly incomplete for the complexity.
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 names the filtering parameters (engine, pricing, type, category) and relates limit to pagination, but does not add significant meaning beyond the schema's own descriptions.
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 searches AI tools for game development, lists supported filters (engine, pricing, type, category), and mentions pagination. It distinguishes itself from the sibling get_tool by focusing on search/filter functionality.
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 use when searching/filtering tools but does not explicitly state when to use this tool versus retrieving a single tool via get_tool. No exclusions or when-not guidance provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_toolAInspect
Get full details of a specific AI tool by its slug from StackFiesta.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | URL slug of the tool (e.g. unity-mcp, meshy) | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only states it gets details. Does not disclose read-only nature, response size, or the required context parameter for analytics. Schema adds context param detail, but tool description lacks behavioral context.
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, 14 words, front-loaded. Efficient but could include more guidance without verbosity. Still earns a 4 for conciseness.
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?
No output schema and description does not explain what 'full details' includes. Unusual context parameter not addressed in tool description. Incomplete for a get-details tool.
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 covers both parameters fully (100%). Tool description adds no extra meaning beyond referencing slug. Baseline 3 due to high schema coverage.
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?
Description clearly states verb (Get), resource (full details of a specific AI tool), method (by slug), and source (StackFiesta). Differentiates from sibling find_tools via 'specific' vs 'find'.
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?
Implies usage when slug is known, but no explicit when-to-use or when-not-to-use compared to find_tools. Lacks guidance on prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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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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