reddit-research
MCP server that answers questions using Reddit discussions as evidence, searching threads, fetching comments, and ranking useful context, with optional cited answer synthesis.
README
reddit-research
A personal-use, retrieval-augmented research tool that answers questions using Reddit discussions as evidence. It searches for relevant threads via a search API, fetches thread/comment data through the official Reddit Data API, ranks the most useful evidence, and returns structured context (optionally synthesized into a cited answer).
It is intended for interactive question answering and short-lived local research. It does not train models on Reddit data, bulk-archive Reddit, or redistribute collected datasets. See the spec for the full design and non-goals.
Install
uv sync # core CLI
uv sync --extra mcp # + MCP server
uv sync --extra dev # + test tooling
Configure
Configuration splits cleanly in two:
-
Secrets → environment /
.env(never the TOML). Copy.env.example:# Reddit creds — only for the "praw" backend (see Fetch backends below) REDDIT_CLIENT_ID=... REDDIT_CLIENT_SECRET=... BRAVE_SEARCH_API_KEY=... # or TAVILY_API_KEY (search always needs a key) ANTHROPIC_API_KEY=... # only if you enable synthesis -
Non-secret behavior →
reddit-research.toml(seereddit-research.example.toml):backend,user_agent, search/synthprovider, comment limits, cache TTLs, etc.
A .env in the current directory (or ~/.config/reddit-research/.env) is loaded
automatically. Precedence is real env var > .env file > TOML > default, so any
TOML value can be overridden by its env var when needed — but each setting has
one canonical home to avoid duplication.
Fetch backends
Reddit gated self-serve API app creation in 2026 (the "Responsible Builder
Policy"), so an approved OAuth app is no longer guaranteed. The fetcher therefore
supports several backends, selectable per-command with --backend or via
[reddit] backend / REDDIT_RESEARCH_BACKEND:
| Backend | Auth | Notes |
|---|---|---|
auto (default) |
— | praw if Reddit creds are set, else arctic |
arctic (recommended keyless) |
none | Arctic Shift archive with PullPush fallback. Works from any IP/host. Serves periodically-updated historical data, so very recent threads may lag; retains deleted/removed content. |
praw |
Reddit OAuth app | Official API; live data + full comment-tree expansion. Needs an approved app. |
json |
none | Reddit's public .json endpoints. Largely unusable in 2026: Reddit fingerprint-blocks the .json path (403) for non-browser clients — even from a residential IP, and even with a matching browser User-Agent (it checks the TLS/HTTP2 fingerprint of a current browser). Kept for the rare environment where it still works. |
reddit-research evidence "..." # auto -> arctic (keyless)
reddit-research answer "..." --backend praw # live data, needs an approved app
Compliance note: arctic/json let you run without an approved app, but using
them to sidestep API approval sits in tension with the spec's "don't circumvent
access controls" non-goal. Intended for genuine personal, low-volume use.
CLI
reddit-research search "best backup strategy for homelab"
reddit-research fetch "https://www.reddit.com/r/selfhosted/comments/..."
reddit-research evidence "what do selfhosted users recommend for backups?" -r selfhosted -r datahoarder
reddit-research answer "what do Reddit users recommend for homelab backups?"
reddit-research cache stats
reddit-research cache purge --older-than-days 30
Useful flags: --subreddit/-r (repeatable), --limit-threads, --max-comments,
--sort, --since-days, --format json|markdown, --no-llm, --show-queries,
--verbose.
MCP server
Exposes search_reddit_threads, fetch_reddit_thread, rank_reddit_evidence,
and the high-level answer_from_reddit. Two transports (REDDIT_RESEARCH_MCP_TRANSPORT):
stdio (default) — local use; the client spawns the process:
{
"mcpServers": {
"reddit-research": {
"command": "reddit-research-mcp",
"env": { "BRAVE_SEARCH_API_KEY": "..." }
}
}
}
http / streamable-http — a long-lived network server for container/NAS
deployment (see below). A bearer token is required; the server refuses to
start over HTTP without REDDIT_RESEARCH_MCP_TOKEN, and every request except
GET /healthz must send Authorization: Bearer <token>.
Deploy on a NAS (Docker)
The included Dockerfile + docker-compose.yml run the MCP server over HTTP.
-
Configure — create
.envnext to the compose file:BRAVE_SEARCH_API_KEY=... # search needs a key REDDIT_RESEARCH_MCP_TOKEN=$(openssl rand -hex 32) # required bearer token # ANTHROPIC_API_KEY=... # only if you enable synthesis -
Run — build from source:
docker compose up -d --build curl http://127.0.0.1:8000/healthz # -> okTo deploy a prebuilt image from your own registry instead, set
REDDIT_RESEARCH_IMAGEin.envand pull:export REGISTRY=your-registry.example.com echo "REDDIT_RESEARCH_IMAGE=$REGISTRY/reddit-research-mcp:latest" >> .env docker login "$REGISTRY" # once docker compose pull && docker compose up -dTo publish a new image after code changes:
docker build --provenance=false \ -t "$REGISTRY/reddit-research-mcp:latest" . docker push "$REGISTRY/reddit-research-mcp:latest"The SQLite cache persists in
./data. The container binds to127.0.0.1:8000by default, so it's reachable only through the NAS's reverse proxy (change theports:mapping to8000:8000to expose it on the LAN instead). -
Reverse proxy (Synology) — Control Panel → Login Portal → Advanced → Reverse Proxy → Create:
- Source:
https://reddit-mcp.<your-domain>(port 443, HTTPS — enables TLS) - Destination:
http://localhost:8000 - Enable HSTS as desired; the streamable-HTTP transport streams responses, so leave response buffering off (the default reverse-proxy behavior is fine).
- Source:
-
Connect from Claude Code:
claude mcp add --transport http reddit-research \ https://reddit-mcp.<your-domain>/mcp \ --header "Authorization: Bearer <your REDDIT_RESEARCH_MCP_TOKEN>"
Security notes: the token gates outbound calls that spend your API keys, so keep
it secret and prefer a random 32-byte value. The compose file sets the keyless
arctic backend (the public .json path is fingerprint-blocked by Reddit for
non-browser clients — see Fetch backends). Switch to praw only if you have an
approved OAuth app and set its credentials in .env.
Architecture
question -> query planner -> search provider -> reddit URL extractor
-> Reddit API fetcher -> cache -> evidence ranker
-> structured evidence -> optional answer synthesis
Package layout under src/reddit_research/:
| Module | Responsibility |
|---|---|
core/config.py |
Env + TOML config, secret handling |
core/models.py |
Pydantic data contracts |
core/search.py |
Query planner + Brave/Tavily providers |
core/reddit.py |
PRAW fetcher + normalization |
core/public_json.py |
Keyless .json fetcher |
core/archive.py |
Arctic Shift / PullPush fetcher |
core/fetchers.py |
Backend selection (auto/praw/json/arctic) |
core/urls.py |
Reddit URL/ID parsing |
core/cache.py |
SQLite cache (TTL + purge) |
core/ranking.py |
Explainable lexical ranking |
core/synth.py |
Optional, provider-agnostic synthesis |
core/orchestrator.py |
Pipeline + run metadata/warnings |
cli.py / mcp_server.py |
Interfaces |
Develop
uv run pytest
Status
MVP implemented: search/fetch/evidence/answer CLI, Brave + Tavily
providers, three fetch backends (praw/json/arctic), SQLite cache, lexical
ranking, JSON/Markdown output, and the MCP server. Later enhancements (async
fetching, semantic reranking, branch summarization) are tracked in the spec.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.