mcpbeat

Redra MCP Server

io.github.sacrosaunt/redra
answering

Redra is answering right now. Last checked 3 min ago. It exposes 5 tools. Last commit 26 Jul 2026.

Search current class-action settlements and identify possible matches using structured filters.

Uptime history 42 hours of history
42 hours agonow
100.0%
Uptime 24h
91 of 91 checks
5
Tools
read from the server
557 ms
Response time
average over 24h
0
Stars
last commit 26 Jul 2026

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 3 min ago.

run in your terminal
claude mcp add redra --transport http https://mcp.redra.ai/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "redra": {
      "url": "https://mcp.redra.ai/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.redra]
url = "https://mcp.redra.ai/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "redra": {
      "url": "https://mcp.redra.ai/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "redra": {
      "url": "https://mcp.redra.ai/mcp"
    }
  }
}

Available tools 5

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

settlements
get_settlements
Return complete stored records for multiple settlement finalists. Retrieve every finalist before presenting it. Use the records and official links to separate evidence-backed leads from plausible or speculative leads. A detail record does not itself prove that the user is eligible. If browsing is available, verify the complete class definition on the official source.
search_settlements
Search settlement records by keywords and structured filters. Every keyword is required: the list uses logical AND, not OR. Use separate searches for unrelated companies, products, or alternative terms. Keywords should describe companies, products, services, employers, incidents, or notices. For a broad eligibility scan, think expansively using relevant context and memory available to the agent and make multiple queries across plausible brands, aliases, parent companies, subsidiaries, purchases, providers, fees, incidents, and eligibility-relevant demographic angles such as age group, occupation, student or veteran status, parent or guardian status, and housing or household situation. Use the state filter for location. Do not invent user facts; speculative associations are search candidates only. Status is the claim lifecycle and defaults to open. Use all only for an intentional search across non-open lifecycle states too. Use settlement_type, not keywords, when the term describes the type of settlement rather than a specific entity or event. Source confidence is returned as objective metadata and quality flags; do not exclude possible matches using the provider's verification tier. Do not send names, addresses, account numbers, health details, or other identifying data. State is a two-letter US postal abbreviation.
search_settlements_batch
Run multiple independent settlement searches in one tool call. Prefer this tool for broad eligibility scans and alternative terms. Each query is evaluated independently. Returned records are deduplicated across queries and include matched_query_indices that point to the query summaries. Do not combine unrelated alternatives in one keywords list: keywords within each query use logical AND, never OR. Speculative associations are search candidates only, not evidence that the user matches a settlement. Choose per-query limits based on expected noise and use max_total_results to bound the unique records placed in model context without reducing search breadth. For current eligibility scans, omit status or set it to open; do not use all merely to broaden recall. The response's executed_query_count is the number of independent searches performed in this call.
dataset
get_dataset_info
Return source, license, freshness, counts, and hosted aggregate metrics.
settlement
get_settlement
Return one settlement and its official source links. When web access is available, use the official links to verify the complete class definition and eligibility terms before presenting the record as more than a possible match. Present plausible matches as concise lead cards that separate confirmed terms, relevant user context, and facts still needed. If browsing is unavailable, say the terms could not be independently checked, avoid guessing, and direct the user to the official link.

Endpoints

URLTransportStateLatencyChecked
https://mcp.redra.ai/mcp streamable-http answering 482 ms 3 min ago

Redra — questions

Answers built from our own checks of this server.

What can Redra do?
It exposes 5 tools, read directly from the server on our last check. Among them: get_dataset_info, get_settlement, get_settlements, search_settlements, search_settlements_batch. 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 Redra 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 557 ms. The bar chart above shows every period we have measured.
How do I connect Redra?
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 Redra need an API key?
No. Redra completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 5 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Redra?
It answers our handshake in 557 ms on average, which is faster than 19% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is Redra open source?
Yes — it is published under the MIT licence, written in Python and 0 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.