ISIS MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OLLAMA_MODEL | No | The Ollama model to use for summarization (e.g., llama3.2:1b, mistral:7b, qwen2.5:0.5b) | llama3.2:1b |
| OLLAMA_TIMEOUT | No | Timeout in milliseconds for Ollama API requests | 30000 |
| OLLAMA_ENDPOINT | No | The endpoint URL for Ollama LLM service used for content summarization | http://localhost:11434 |
| SCRAPER_API_KEY | No | Optional API key for ScraperAPI (paid fallback search provider) |
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| ragB | Busca web com extração inteligente de conteúdo (igual Apify RAG Web Browser) |
| fetchFullContentB | Busca conteúdo completo de um resultado anterior de RAG obtido em contentMode=preview |
| scrapeC | Extrai conteúdo inteligente de uma URL específica |
| screenshotC | Captura screenshot de uma página web |
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
The tools have some overlap in purpose, particularly between 'rag' (web search with content extraction) and 'scrape' (extract content from a specific URL), which could cause confusion about when to use each. However, 'fetchFullContent' and 'screenshot' are more distinct, targeting specific retrieval and visual capture tasks, respectively.
The naming conventions are mixed: 'fetchFullContent' uses camelCase, while 'rag', 'scrape', and 'screenshot' use lowercase. There is no consistent verb_noun pattern, but the names are still readable and descriptive of their functions.
With 4 tools, the server is well-scoped for web content retrieval and extraction tasks. Each tool appears to serve a specific purpose without redundancy, making the count appropriate for the domain of web scraping, searching, and screenshot capture.
The tool set covers core web content operations: searching ('rag'), scraping from URLs ('scrape'), retrieving full content ('fetchFullContent'), and visual capture ('screenshot'). A minor gap might be the lack of tools for processing or analyzing the extracted content, but the basic retrieval and extraction workflows are well-covered.