glama-gateway-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GLAMA_API_KEY | Yes | Your Glama API key | |
| GLAMA_DEFAULT_MODEL | No | Optional default model to use, e.g. openai/gpt-4o |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| glama_list_modelsA | List the models available through the Glama gateway (OpenAI-format model ids). |
| glama_chat_completionC | Run a chat completion against the Glama gateway. |
| glama_stream_completionB | Streamed chat completion; deltas are reassembled into one text answer with usage metadata. |
| glama_request_statusC | Look up the status of a completion request by id. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
list_models and request_status are clearly distinct, but chat_completion and stream_completion overlap in purpose as they both perform chat completions. The descriptions clarify streaming vs. non-streaming, so an agent can differentiate them, though some ambiguity remains.
All tool names share the glama_ prefix and follow a consistent snake_case verb_noun pattern. The naming is predictable and uniform across the set.
Four tools is well-scoped for a gateway-focused server covering model discovery, completion, streaming, and status lookup. Each tool has a clear, non-redundant role.
The core workflow of listing models and running both standard and streaming completions is covered, plus status lookup for async requests. Minor additions like request cancellation or model details would improve completeness, but no critical gap exists.