Freellmpool vs Gammainfra MCP Server
A side-by-side look at the Freellmpool and Gammainfra MCP Server MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Freellmpool for conversational ai work as a local process; choose Gammainfra MCP Server for conversational ai as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Freellmpool when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
Choose Gammainfra MCP Server when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
GAMMAINFRA_API_KEY, GAMMAINFRA_BASE_URL. - You want tools like
model, messages, temperature.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 45/100 · Fair | 49/100 · Fair |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | GAMMAINFRA_API_KEYGAMMAINFRA_BASE_URL |
| Verified owner | Community listing | Community listing |
| GitHub stars | 127 | 0 |
| Directory activity | 0 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | Not listed | 10 |
| Full listing | View Freellmpool | View Gammainfra MCP Server |
Tools & capabilities
Freellmpool tools
No tool names declared yet. Check the project README from the listing page.
Gammainfra MCP Server tools 10
modelgammainfra/auto` for smart routing, `gammainfra/fast`/`gammainfra/cheap` for tier shortcuts, or pin a specific model like `openai/gpt-5-mini`.messagesOpenAI-shape conversation messages.temperature0..2.max_tokensmax_completion_tokensGPT-5 family requires this instead of `max_tokens`.cost_quality0.0..1.0 continuous dial. Sent as `X-GammaInfra-Cost-Quality`.max_latency_ms60..600000. Caps total wall-clock incl. fallback retries. Also enforced client-side as a hard request abort.preferencequality`, `cost`, or `latency`.regionus`, `eu`, `apac`, or specific AWS region.include_byokDefault `false`. Also fetch the BYOK balance. Off by default to avoid an extra request — and a guaranteed 404 — for customers without BYOK enrollment.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Freellmpool
{
"mcpServers": {
"freellmpool": {
"command": "uvx",
"args": [
"freellmpool"
]
}
}
}
Gammainfra MCP Server
{
"mcpServers": {
"mcp-server-27": {
"command": "npx",
"args": [
"-y",
"@gammainfra/mcp-server"
],
"env": {
"GAMMAINFRA_API_KEY": "YOUR_GAMMAINFRA_API_KEY_HERE",
"GAMMAINFRA_BASE_URL": "YOUR_GAMMAINFRA_BASE_URL_HERE"
}
}
}
}
Frequently asked questions
Freellmpool is categorized under Conversational AI and uses a local stdio subprocess. Gammainfra MCP Server belongs to Conversational AI and uses a local stdio subprocess. Pick Freellmpool for conversational ai work and Gammainfra MCP Server for conversational ai.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Freellmpool has no declared pricing — check the project's own site. Gammainfra MCP Server has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add freellmpool and mcp-server-27 as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Freellmpool has a quality signal of 45/100 (Fair) with 0 views, 0 installs and 127 GitHub stars. Gammainfra MCP Server has 49/100 (Fair) with 0 views, 0 installs and 0 GitHub stars.