Kagi MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| KAGI_API_KEY | Yes | Your Kagi API key |
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
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| ask_fastgptC | Ask fastgpt to search web and give an answer with references |
| enrich_webC | Enrich context with web content focused on general, non-commercial web content. |
| enrich_newsC | Enrich context with web content focused on non-commercial news and discussions. |
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 3 tools
The three tools have overlapping purposes that could cause confusion. 'enrich_news' and 'enrich_web' both enrich context with web content, differing mainly in focus (news vs general), which may not be clear to an agent. 'ask_fastgpt' also involves web content for answers, creating ambiguity in tool selection.
The naming follows a consistent verb_noun pattern throughout (ask_fastgpt, enrich_news, enrich_web), which is predictable and readable. There are no deviations in style, making it easy to parse.
With only 3 tools, the count feels thin for a web search and enrichment server, potentially limiting functionality. While not extreme, it may lack coverage for common operations like filtering or managing searches.
The tool set has significant gaps for a web content server. There are no tools for basic operations like searching without enrichment, filtering results, or handling different content types beyond news and general web. This could lead to agent failures when trying to perform common tasks.