Ai·rete·rag vs MCP Local Rag
A side-by-side look at the Ai·rete·rag and MCP Local Rag MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Ai·rete·rag for knowledge & memory work as a local process; choose MCP Local Rag for knowledge & memory as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Ai·rete·rag when
- You need dedicated capabilities in the Knowledge & Memory domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
AI_RETE_RAG_API_KEY, AI_RETE_RAG_API_URL. - You want tools like
decide, get_parameters, list_rules.
Choose MCP Local Rag when
- You need dedicated capabilities in the Knowledge & Memory domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You have the keys it needs:
BASE_DIR, BASE_DIRS, IGNORE_PATHS, DB_PATH, CACHE_DIR, HF_ENDPOINT. - You want tools like
sync_start, sync_status, ingest_file.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Knowledge & Memory | Knowledge & Memory |
| Quality signal | 52/100 · Good | 69/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | AI_RETE_RAG_API_KEYAI_RETE_RAG_API_URL | BASE_DIRBASE_DIRSIGNORE_PATHSDB_PATHCACHE_DIRHF_ENDPOINT |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 421 |
| Directory activity | 0 views 0 installs 0 upvotes | 14 views 0 installs 0 upvotes |
| Tools | 9 | 9 |
| Full listing | View Ai·rete·rag | View MCP Local Rag |
Tools & capabilities
Ai·rete·rag tools 9
decideMake a decision in a domain — structured facts and/or free text, with optional Pattern 01 (rules scope retrieval) and Pattern 02 (retrieval into working memory). `as_of` reads the policy documents in force on an earlier dayget_parametersThe facts a domain's rules decide on (from your account's own rules), most decisive first — what to collect before `decidelist_rulesInspect a domain's rules — conditions, verdicts, salience, overlapsget_rule_sourceFetch a domain's rule set as editable YAMLimport_policy_rulesTurn a written policy document into draft rules, each citing the sentence it encodes (nothing is saved — review, then `put_rules`)put_rulesCreate or replace a domain's rule set from YAML (dry_run to validate)ingest_textAdd policy text to a domain's knowledge base, optionally dated (`effective_from`, `effective_until`) or replacing an earlier version (`supersedes`)list_documentsBrowse a domain's ingested documentsget_usageCheck your plan and remaining monthly decision quota
MCP Local Rag tools 9
sync_startReconcile the index with all configured roots or one pathsync_statusPoll a running sync jobingest_fileIngest or replace one fileingest_dataIngest text, Markdown, or HTML already held by the clientquery_documentsSearch with semantic matching and keyword boostread_chunk_neighborsRead surrounding chunks from a search resultlist_filesShow supported files and their ingestion statedelete_fileDelete an indexed file or an `ingest_data` itemstatusShow index and search status
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Ai·rete·rag
{
"mcpServers": {
"ai-rete-rag-2": {
"command": "uvx",
"args": [
"ai-rete-rag-mcp"
],
"env": {
"AI_RETE_RAG_API_KEY": "YOUR_AI_RETE_RAG_API_KEY_HERE",
"AI_RETE_RAG_API_URL": "YOUR_AI_RETE_RAG_API_URL_HERE"
}
}
}
}
MCP Local Rag
{
"mcpServers": {
"shinpr-mcp-local-rag": {
"command": "npx",
"args": [
"-y",
"mcp-local-rag"
],
"env": {
"BASE_DIR": "YOUR_BASE_DIR_HERE",
"BASE_DIRS": "YOUR_BASE_DIRS_HERE",
"IGNORE_PATHS": "YOUR_IGNORE_PATHS_HERE",
"DB_PATH": "YOUR_DB_PATH_HERE",
"CACHE_DIR": "YOUR_CACHE_DIR_HERE",
"HF_ENDPOINT": "YOUR_HF_ENDPOINT_HERE"
}
}
}
}
Frequently asked questions
Ai·rete·rag is categorized under Knowledge & Memory and uses a local stdio subprocess. MCP Local Rag belongs to Knowledge & Memory and uses a local stdio subprocess. Pick Ai·rete·rag for knowledge & memory work and MCP Local Rag for knowledge & memory.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Ai·rete·rag has no declared pricing — check the project's own site. MCP Local Rag is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add ai-rete-rag-2 and shinpr-mcp-local-rag as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Ai·rete·rag has a quality signal of 52/100 (Good) with 0 views, 0 installs and 0 GitHub stars. MCP Local Rag has 69/100 (Great) with 14 views, 0 installs and 421 GitHub stars.