ACR MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| memory_searchC | Keyword search over ACR's local memory store. |
| skill_searchB | Keyword search over ACR's local skill registry. |
| web_fetchC | Fetch a URL over HTTP(S) and return its extracted text. |
| github_searchC | Search GitHub issues and pull requests (read-only). |
| browser_fetchB | Render a URL in a real headless browser and return its visible text, including JS-rendered content web_fetch can't see. |
| run_taskB | Run an objective through ACR's task engine. Uses the zero-config mock provider unless min_quality_tier is raised (or Settings.default_min_quality_tier is configured) to prefer a configured Ollama/cloud provider instead. |
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 6 tools
Each tool targets a distinct domain: memory search, skill search, web fetching (two variants), GitHub search, and task execution. No overlaps exist.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., memory_search, web_fetch, run_task), with clear prefixes for related operations.
Six tools provide a focused set covering search, fetch, and task execution without being excessive or minimal.
Significant gaps exist: memory and skill stores only support search (no create/update/delete), and run_task lacks status or result retrieval, limiting the workflow.