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
- Repository
- stackfiesta/stackfiesta-mcp
- GitHub Stars
- 0
- Server Listing
- StackFiesta MCP Server
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 3.5/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one for searching/filtering tools and one for retrieving details of a specific tool. There is no overlap in functionality.
Both tool names follow a consistent verb_noun pattern using snake_case: find_tools and get_tool. The naming convention is uniform and predictable.
With only two tools, the server is borderline thin. While the tools cover basic search and retrieval, the scope feels limited for a catalog service.
The set includes search and detail retrieval but lacks other operations like listing categories or browsing all tools without filters. Minor gaps exist that agents can work around.
Available Tools
2 toolsfind_toolsAInspect
Find AI tools for game development from the StackFiesta catalog. Filter by engine, pricing, type, and category.
| 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?
No annotations are provided, so the description carries the full burden. It only states the purpose without disclosing any non-obvious behavior such as authentication needs, rate limits, or side effects. It does not contradict annotations.
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, clear sentence with no wasted words. Every part 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?
The description covers the basic purpose and filters, but for a search tool with 7 parameters and no output schema, it lacks details on return format, pagination, or how to effectively use the 'query' and 'context' parameters.
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 coverage is 100%, so baseline is 3. The description adds meaning by listing four filterable fields (engine, pricing, type, category) but does not mention the 'limit', 'query', or 'context' parameters. It provides partial additional context.
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 finds AI tools for game development from the StackFiesta catalog and mentions filtering capabilities. It distinguishes itself from the sibling 'get_tool' by implying a search/find function.
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 searching tools with filters but does not explicitly state when to use this tool versus the sibling 'get_tool' or provide any usage context or exclusions.
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.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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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
Centralized credential management – store and rotate API keys and OAuth tokens in one place
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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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