MCP server that gives your AI assistant research tools. Google search, Reddit deep-dives, web scraping with LLM extraction, and multi-model deep research — all as MCP tools that chain into each other.
```bash
npx mcp-researchpowerpack
```
five tools, zero config to start. each API key you add unlocks more capabilities.
[](https://www.npmjs.com/package/mcp-researchpowerpack)
[](https://nodejs.org/)
[](https://opensource.org/licenses/MIT)
---
## tools
| tool | what it does | requires |
|:---|:---|:---|
| `web_search` | parallel Google search across 3-100 keywords, CTR-weighted ranking, consensus detection | `SERPER_API_KEY` |
| `search_reddit` | same engine but filtered to reddit.com, 10-50 queries in parallel | `SERPER_API_KEY` |
| `get_reddit_post` | fetches 2-50 Reddit posts with full comment trees, optional LLM extraction | `REDDIT_CLIENT_ID` + `REDDIT_CLIENT_SECRET` |
| `scrape_links` | scrapes 1-50 URLs with JS rendering fallback, HTML-to-markdown, optional LLM extraction | `SCRAPEDO_API_KEY` |
| `deep_research` | sends questions to research-capable models (Grok, Gemini) with web search enabled, supports local file attachments | `OPENROUTER_API_KEY` |
tools are designed to chain: `web_search` suggests calling `scrape_links`, which suggests `search_reddit`, which suggests `get_reddit_post`, which suggests `deep_research` for synthesis.
## install
### Claude Desktop / Claude Code
add to your MCP config:
```json
{
"mcpServers": {
"research-powerpack": {
"command": "npx",
"args": ["mcp-researchpowerpack"],
"env": {
"SERPER_API_KEY": "...",
"OPENROUTER_API_KEY": "..."
}
}
}
}
```
### from source
```bash
git clone https://github.com/yigitkonur/mcp-research-powerpack.git
cd mcp-research-powerpack
pnpm install && pnpm build
pnpm start
```
### HTTP mode
```bash
MCP_TRANSPORT=http MCP_PORT=3000 npx mcp-researchpowerpack
```
exposes `/mcp` (POST/GET/DELETE with session headers) and `/health`.
## API keys
each key unlocks a capability. missing keys silently disable their tools — the server never crashes.
| variable | enables | free tier |
|:---|:---|:---|
| `SERPER_API_KEY` | `web_search`, `search_reddit` | 2,500 searches/mo at serper.dev |
| `REDDIT_CLIENT_ID` + `REDDIT_CLIENT_SECRET` | `get_reddit_post` | unlimited (reddit.com/prefs/apps, "script" type) |
| `SCRAPEDO_API_KEY` | `scrape_links` | 1,000 credits/mo at scrape.do |
| `OPENROUTER_API_KEY` | `deep_research`, LLM extraction in scrape/reddit | pay-per-token at openrouter.ai |
## configuration
optional tuning via environment variables:
| variable | default | description |
|:---|:---|:---|
| `RESEARCH_MODEL` | `x-ai/grok-4-fast` | primary deep research model |
| `RESEARCH_FALLBACK_MODEL` | `google/gemini-2.5-flash` | fallback if primary fails |
| `LLM_EXTRACTION_MODEL` | `openai/gpt-oss-120b:nitro` | default model for scrape/reddit LLM extraction (can be overridden per-request via the `model` parameter in `scrape_links`) |
| `DEFAULT_REASONING_EFFORT` | `high` | research depth (`low`, `medium`, `high`) |
| `DEFAULT_MAX_URLS` | `100` | max search results per research question (10-200) |
| `API_TIMEOUT_MS` | `1800000` | request timeout in ms (default 30 min) |
| `MCP_TRANSPORT` | `stdio` | `stdio` or `http` |
| `MCP_PORT` | `3000` | port for HTTP mode |
## how it works
### search ranking
results from multiple queries are deduplicated by normalized URL and scored using CTR-weighted position values (position 1 = 100.0, position 10 = 12.56). URLs appearing across multiple queries get a consensus marker. threshold tries >= 3, falls back to >= 2, then >= 1.
### Reddit comment budget
global budget of 1,000 comments, max 200 per post. after the first pass, surplus from posts with fewer comments is redistributed to truncated posts in a second fetch pass.
### scraping pipeline
three-mode fallback per URL: basic → JS rendering → JS + US geo-targeting. results go through HTML-to-markdown conversion (turndown), then optional LLM extraction with a 100k char input cap and 8,000 token output per URL. the extraction model defaults to `openai/gpt-oss-120b:nitro` (configurable via `LLM_EXTRACTION_MODEL` env var) and can be overridden per-request using the `model` parameter.
### deep research
32,000 token budget divided across questions (1 question = 32k, 10 questions = 3.2k each). Gemini models get `google_search` tool access. Grok/Perplexity get `search_parameters` with citations. primary model fails → automatic fallback.
### file attachments
`deep_research` can read local files and include them as context. files over 600 lines are smart-truncated (first 500 + last 100 lines). line numbers preserved.
## concurrency
| operation | parallel limit |
|:---|:---|
| web search keywords | 8 |
| Reddit search queries | 8 |
| Reddit post fetches per batch | 5 (batches of 10) |
| URL scraping per batch | 10 (batches of 30) |
| LLM extraction | 3 |
| deep research questions | 3 |
all clients use manual retry with exponential backoff and jitter. the OpenAI SDK's built-in retry is disabled (`maxRetries: 0`).
## project structure
```
src/
index.ts — entry point, STDIO + HTTP transport, signal handling
worker.ts — Cloudflare Workers entry (Durable Objects)
config/
index.ts — env parsing (lazy Proxy objects), capability detection
loader.ts — YAML → Zod → JSON Schema pipeline, cached
yaml/tools.yaml — single source of truth for all tool definitions
schemas/
deep-research.ts — Zod validation for research questions + file attachments
scrape-links.ts — Zod validation for URLs, timeout, LLM options
web-search.ts — Zod validation for keyword arrays
tools/
registry.ts — tool lookup → capability check → validate → execute
search.ts — web_search handler
reddit.ts — search_reddit + get_reddit_post handlers
scrape.ts — scrape_links handler
research.ts — deep_research handler
clients/
search.ts — Serper API client
reddit.ts — Reddit OAuth + comment fetching
scraper.ts — scrape.do client with fallback modes
research.ts — OpenRouter client with model-specific handling
services/
llm-processor.ts — shared LLM extraction (singleton OpenAI client)
markdown-cleaner.ts — HTML → markdown via turndown
file-attachment.ts — local file reading with line ranges
utils/
concurrency.ts — bounded parallel execution (pMap, pMapSettled)
url-aggregator.ts — CTR-weighted scoring and consensus detection
errors.ts — error classification, fetchWithTimeout
logger.ts — MCP logging protocol
response.ts — standardized output formatting
```
## deploy
### Cloudflare Workers
```bash
npx wrangler deploy
```
uses Durable Objects with SQLite storage. YAML-based tool definitions are replaced with inline definitions in the worker entry since there's no filesystem.
## license
MIT
