Agentic RL: Credit Assignment and CLI Agents MCP Server

by hf-hoyant-su-agentic-rl Your server? Claim it

answering

Agentic RL: Credit Assignment and CLI Agents is answering right now. Last checked 12 min ago. It exposes 8 tools.

Filter agent RL methods by supervision, critic and task setting; retrieve source links and BibTeX.

Uptime history 17 days of history

17 days agonow

100.0%

Uptime 24h

91 of 91 checks

Tools

read from the server

325 ms

Response time

average over 24h

open, no key

Access

streamable-http

What changed 5

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 8 September 2026. No other catalogue keeps this.

8 Sep 3 tool descriptions were rewritten Agentic_RL_dataset_overview, Agentic_RL_list_sources, Agentic_RL_search_evidence

8 Sep 2 tools appeared Agentic_RL_filter_methods, Agentic_RL_list_method_facets

Nothing serious here today

Today is the operative word: we check Agentic RL: Credit Assignment and CLI Agents every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 12 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add agentic-rl --transport http https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "agentic-rl": {
      "url": "https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/"
    }
  }
}

~/.codex/config.toml

[mcp_servers.agentic-rl]
url = "https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/"

.cursor/mcp.json

{
  "mcpServers": {
    "agentic-rl": {
      "url": "https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/"
    }
  }
}

.vscode/mcp.json

{
  "mcpServers": {
    "agentic-rl": {
      "url": "https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/"
    }
  }
}

Available tools 8

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

agentic

Agentic_RL_dataset_overview

Inspect ShellOps and ShellOps-Pro task counts, train/test splits, task types, published schemas, source files, license and citation.

Agentic_RL_fetch_evidence

Fetch a complete original evidence block by the evidence_id returned from search_evidence, including section anchor, version, equations, table cells, links, and attribution.

Agentic_RL_filter_methods

Filter agent RL credit-assignment methods by research conditions and return original section evidence and BibTeX. Discover accepted values with list_method_facets. Filters combine with AND; empty strings leave a facet unrestricted. Unknown critic status never matches no. Results use publication order without a relevance or quality ranking.

Agentic_RL_get_task

Inspect one published ShellOps or ShellOps-Pro task by its exact task_id and partition ('shellops' or 'shellops_pro'). Returns the complete instruction, actual reward specification, published reference answer/command, file-entry metadata, pinned parquet rows and workspace asset links. File content is available at the source links. No shell execution or solution verification is performed.

Agentic_RL_list_method_facets

List exact filter values for agent RL credit granularity, supervision, value critics and evaluation settings. Each value reports its source-supported method count.

Agentic_RL_list_sources

List original papers and retrieval coverage. Discover source-linked comparisons of credit assignment, agent memory, selective observation and terminal benchmarks, with JSON, CSV and BibTeX links.

Agentic_RL_search_evidence

Search original papers on agentic reinforcement learning, credit assignment and CLI agents. Use English keywords (AND), OR and quoted phrases. Return relevant passages, source citations, equations and table cells.

Agentic_RL_search_tasks

Find real ShellOps CLI benchmark tasks by case-insensitive literal substring in the complete instruction, task ID or published task type. Empty query lists all tasks. Select partition 'all', 'shellops' or 'shellops_pro'; select published split 'all', 'train_src', 'train' or 'test'. Results are ordered by partition then task ID, with explicit pagination and no relevance scoring. The train subset is not double-counted.

Endpoints

URL	Transport	State	Latency	Checked
https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/	streamable-http	answering	320 ms	12 min ago

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Agentic RL: Credit Assignment and CLI Agents — questions

Answers built from our own checks of this server.

What can Agentic RL: Credit Assignment and CLI Agents do?

It exposes 8 tools, read directly from the server on our last check. Among them: Agentic_RL_dataset_overview, Agentic_RL_fetch_evidence, Agentic_RL_filter_methods, Agentic_RL_get_task, Agentic_RL_list_method_facets, Agentic_RL_list_sources and 2 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

Is Agentic RL: Credit Assignment and CLI Agents working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 325 ms. The bar chart above shows every period we have measured.

How do I connect Agentic RL: Credit Assignment and CLI Agents?

Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does Agentic RL: Credit Assignment and CLI Agents need an API key?

No. Agentic RL: Credit Assignment and CLI Agents completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 8 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is Agentic RL: Credit Assignment and CLI Agents?

It answers our handshake in 325 ms on average, which is faster than 54% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.