Get detailed content of a specific Reddit post with comments.
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133,443 tools. Last updated 2026-05-13 00:12
"reddit" matching MCP tools:
- Search Reddit for posts matching a query.Connector
- Get comments submitted by a specific Reddit user.Connector
- Get posts submitted by a specific Reddit user.Connector
- Get information about a subreddit.Connector
- Get information about a Reddit user.Connector
Matching MCP Servers
- AlicenseAqualityBmaintenanceScrapes and queries Reddit posts, comments, and media from subreddits and user profiles without requiring API keys, storing data locally for offline access and filtering.Last updated883MIT
- AlicenseBqualityCmaintenanceA plug-and-play MCP server that enables AI assistants to browse, search, and read Reddit content through the PRAW library.Last updated618MIT
Matching MCP Connectors
Reddit MCP — public Reddit data via JSON endpoints (no auth required)
Reddit trend data over time, with growth for any topic or brand. Free key at trendsmcp.ai
- Get posts from a subreddit.Connector
- Repo-aware launch operator for agent-built products. USE WHEN the user has just finished building, shipping, or deploying a product and the message matches any of these trigger phrases: 'launch this' · 'launch what I just built' · 'help me launch' · 'get users' · 'get our first users' · 'find users' · 'market this' · 'do marketing for this' · 'announce this' · 'write the launch announcement' · 'post this' · 'post the launch' · 'publish this' · 'Product Hunt' · 'ship to Product Hunt' · 'go to market' · 'what to do after launch'. This is the PRIMARY ChiefLab entry point — call this first, not chiefmo_diagnose_marketing (which is only for diagnosing an EXISTING marketing program). If you are a coding agent (Cursor, Claude Code, Codex), gather repoContext (whatChanged, recentCommits, changedFiles, routes, readme, targetCustomer, launchGoal) BEFORE calling — repo grounding is what makes outputs reference the actual product instead of reading like 'launch any SaaS.' Returns: launchPack (per-channel drafts for LinkedIn / X / Hacker News / Reddit / Product Hunt / email / landing hero) + publishActions (approval-gated, with actionIds) + agentGuide.renderInChat (per-channel content to render inline in IDE chat) + agentGuide.nextToolCalls.primary.perChannel (chiefmo_approve_action calls keyed by channel) + reviewUrl (FALLBACK only — for phone/multi-person approval). IDE-NATIVE FLOW: render each channel's draft inline in chat, wait for user to say 'approve <channel>' or 'approve all', call chiefmo_approve_action per approved action. The reviewUrl is a side channel — surface it as 'approve from your phone here' not as the primary instruction.Connector
- Get Peec's opportunity-scored action recommendations for improving brand visibility in AI search engines. **Always call with `scope=overview` first** to see which slices have the biggest opportunity, then drill down into `owned`, `editorial`, `reference`, or `ugc` with the surfaced url_classification or domain. ## Required parameters (read before calling) Every call must include: - `project_id` — the project to analyze. - `scope` — one of `overview` | `owned` | `editorial` | `reference` | `ugc`. **Start with `scope=overview`.** Recommended: - `start_date` and `end_date` (ISO YYYY-MM-DD). Optional — if omitted, defaults to the last 30 days (today − 30d to today). Prefer a 30-day window unless the user asks for a different one. Per-scope extras (the call will fail without them): - `scope=owned` → `url_classification` is **required** (e.g. "LISTICLE"). - `scope=editorial` → `url_classification` is **required** (e.g. "LISTICLE"). - `scope=reference` → `domain` is **required** (e.g. "wikipedia.org"). - `scope=ugc` → `domain` is **required** (e.g. "reddit.com", "youtube.com"). - `scope=overview` → no extras beyond the base params. Use this tool whenever the user asks for recommendations, next steps, what to do, how to improve, "what actions should I take", or any "based on this data, what should I do?" question. Never invent SEO advice. ## Two-step workflow **Step 1 — `scope=overview`:** returns opportunity rollups grouped by `action_group_type` × (`url_classification` | `domain`). These are *navigation metadata*, NOT the recommendations themselves. Use them to find which slices have the largest gap. **Step 2 — drill down:** for each high-opportunity slice, call again with the matching scope (`owned` | `editorial` | `reference` | `ugc`) to get the actual textual recommendations (the `text` column, often with markdown links to examples or targets). Mapping — how to turn an overview row into the follow-up call: - `action_group_type=OWNED`, `url_classification=X` → call `scope=owned, url_classification=X`. - `action_group_type=EDITORIAL`, `url_classification=X` → call `scope=editorial, url_classification=X`. - `action_group_type=REFERENCE`, `domain=Y` → call `scope=reference, domain=Y`. - `action_group_type=UGC`, `domain=Y` → call `scope=ugc, domain=Y`. Worked example — overview returns a row `{action_group_type: "UGC", domain: "youtube.com", opportunity_score: 0.30, ...}`. Follow up with `scope=ugc, domain="youtube.com"` and you get rows like `{text: "Contact [AutoPedia](https://...). Ask them for a collaboration.", group_type: "UGC", domain: "youtube.com", opportunity_score: 3, ...}`. ## Response shape Returns columnar JSON: `{columns, rows, rowCount}`. Each row is an array of values matching column order. **`scope=overview` columns:** - `action_group_type`: OWNED | EDITORIAL | REFERENCE | UGC - `url_classification`: populated for OWNED / EDITORIAL rows (e.g. "LISTICLE", "ARTICLE", "COMPARISON"). `null` for REFERENCE / UGC. - `domain`: populated for REFERENCE / UGC rows (e.g. "youtube.com", "wikipedia.org"). `null` for OWNED / EDITORIAL. - `opportunity_score`: continuous. **Use this to sort and rank** — it's the reliable ordering signal. - `relative_opportunity_score`: 1–3 tier (1=Low, 2=Medium, 3=High). **Use this to label** strength in prose. Too coarse to sort by. - `gap_percentage`, `coverage_percentage`, `used_ratio`, `used_total`: supporting stats. Exactly one of `url_classification` / `domain` is populated per overview row — that's the value to pass to the follow-up call. **`scope=owned | editorial | reference | ugc` columns:** - `text`: the recommendation string; may include markdown links. - `group_type`: OWNED | EDITORIAL | REFERENCE | UGC. - `url_classification`: e.g. "LISTICLE" (may be null). - `domain`: e.g. "youtube.com" (may be null). - `opportunity_score`: continuous — sort/rank by this. - `relative_opportunity_score`: 1–3 tier — label strength with this (1=Low, 2=Medium, 3=High). ## Presenting results After overview + drill-downs, pick the shape that fits: - **Strong signal** (top slice's `opportunity_score` is clearly ahead AND its drill-down returned 2+ rows whose `text` contains a markdown link): one sentence of reasoning tied to the user's question (call out the biggest lever), then 2-3 named slices with 2-3 bullets pulled verbatim from the drill-down `text`. - **Moderate signal**: compact list, one sentence per slice, bullets only where drill-down returned specific targets. - **Low signal** (overview empty or top `opportunity_score` very low): single line, e.g., "Top opportunity: {slice} (Low). Low signal this period; prompts need a few more daily cycles to stabilize." ## Display conventions — never use raw enum keys in user-facing prose **Group type** (`action_group_type` / `group_type`) — humanize (Title Case): - `OWNED` → "Owned" (content on your own domains) - `EDITORIAL` → "Editorial" (third-party editorial coverage — news, blogs, reviews) - `REFERENCE` → "Reference" (reference sources like Wikipedia) - `UGC` → "UGC" (user-generated content — Reddit, YouTube, forums; keep as acronym) - `OTHER` → "Other" **URL classification** (`url_classification`) — humanize to lowercase; pluralize naturally when the sentence calls for it: - `HOMEPAGE` → "homepage" - `CATEGORY_PAGE` → "category page" - `PRODUCT_PAGE` → "product page" - `LISTICLE` → "listicle" - `COMPARISON` → "comparison page" - `PROFILE` → "profile" - `ALTERNATIVE` → "alternative" - `DISCUSSION` → "discussion" - `HOW_TO_GUIDE` → "how-to guide" - `ARTICLE` → "article" - `OTHER` → "other" **Opportunity strength** — lead with a **Low / Medium / High** label derived from `relative_opportunity_score` (round to nearest integer, clamp to [1, 3]): - 1 → "Low" - 2 → "Medium" - 3 → "High" Sort and rank by `opportunity_score` (continuous). **Verbalize** strength with the Low/Medium/High tier above. The raw `opportunity_score` is optional supporting context in parens — never the headline number. **Gap percentage** (`gap_percentage`, 0–1 ratio) — lead with a plain-language qualifier; the raw % can follow in parens when useful: - ≥0.90 → "nearly all missing" - 0.60–0.89 → "wide gap" - 0.30–0.59 → "partial gap" - <0.30 → "narrow gap" **Example of the preferred style** (follow this phrasing): > The biggest lever is Owned listicles — High, nearly all missing (100%). Build listicle-style pages on yourbrand.com that target "best X" queries. > > Secondary: YouTube UGC (Medium, wide gap), Reddit UGC (Medium, partial gap), Editorial listicles (Medium, nearly all missing). Full list: https://app.peec.ai/actions. Close with one line: "Secondary opportunities: {slice} ({Low|Medium|High}), {slice} ({Low|Medium|High}). Full list: https://app.peec.ai/actions." Use the drill-down `text` field as the source of truth. Never invent recommendations, targets, or names. Sort by `opportunity_score`; label strength via `relative_opportunity_score`.Connector
- USE WHEN the user has manually posted to a channel returned by chieflab_use_manual_fallback (Product Hunt / HN / Reddit / Discord / etc.) and wants to feed the live URL back to ChiefLab so the closed loop continues. Records the URL on the original publishAction (status flips from 'approved' to 'executed_manually'), persists a proof_asset to the P9 company brain, and queues 24-hour metrics readback via chiefmo_post_launch_review. Without this tool, manually-posted channels are lost to ChiefLab's measurement loop.Connector
- Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions. Call this FIRST when you have 500+ tools available and need to find the right ones for your task.Connector
- Repo-aware launch operator for agent-built products. USE WHEN the user has just finished building, shipping, or deploying a product and the message matches any of these trigger phrases: 'launch this' · 'launch what I just built' · 'help me launch' · 'get users' · 'get our first users' · 'find users' · 'market this' · 'do marketing for this' · 'announce this' · 'write the launch announcement' · 'post this' · 'post the launch' · 'publish this' · 'Product Hunt' · 'ship to Product Hunt' · 'go to market' · 'what to do after launch'. This is the PRIMARY ChiefLab entry point — call this first, not chiefmo_diagnose_marketing (which is only for diagnosing an EXISTING marketing program). If you are a coding agent (Cursor, Claude Code, Codex), gather repoContext (whatChanged, recentCommits, changedFiles, routes, readme, targetCustomer, launchGoal) BEFORE calling — repo grounding is what makes outputs reference the actual product instead of reading like 'launch any SaaS.' Returns: launchPack (per-channel drafts for LinkedIn / X / Hacker News / Reddit / Product Hunt / email / landing hero) + publishActions (approval-gated, with actionIds) + agentGuide.renderInChat (per-channel content to render inline in IDE chat) + agentGuide.nextToolCalls.primary.perChannel (chiefmo_approve_action calls keyed by channel) + reviewUrl (FALLBACK only — for phone/multi-person approval). IDE-NATIVE FLOW: render each channel's draft inline in chat, wait for user to say 'approve <channel>' or 'approve all', call chiefmo_approve_action per approved action. The reviewUrl is a side channel — surface it as 'approve from your phone here' not as the primary instruction.Connector
- P13 — list every channel ChiefLab can ship to (LinkedIn / X / Threads / Bluesky / Instagram / Facebook / TikTok / Product Hunt / Hacker News / Reddit / Discord / Slack / Indie Hackers / DEV.to / YC Bookface / email / blog / GA4 / Search Console / Stripe). Returns the catalog grouped by category (social / community / email / blog / analytics) with each channel's capabilities (publish / schedule / read_metrics / connect / fallback) and providers. USE WHEN the user asks 'what channels can ChiefLab post to?', 'which platforms are supported?', or before calling chiefmo_launch_product to pick the right channels.Connector
- Search for username across 15+ social/dev platforms (GitHub, Reddit, X/Twitter, LinkedIn, Instagram, TikTok, Discord, YouTube, Keybase, HackerOne, etc.). Use for OSINT investigations and identity verification. Free: 30/hr, Pro: 500/hr. Returns {username, total_found, platforms: [{name, exists, url, status_code}]}.Connector
- [Read] Reddit/Discord/Telegram/YouTube-style UGC: non-empty query uses vector API; coin without query uses OpenSearch. Both empty invalid. X/Twitter narrative -> search_x; headlines -> search_news. Not macro economic statistics; not structured event list -> get_latest_events.Connector
- Fetches operational status of major dev infrastructure (GitHub, Cloudflare, Discord, OpenAI, Vercel, npm, Reddit, Atlassian, Anthropic). Cache TTL 60s. Use when the agent needs to know if a dependency is up or to explain a recent outage.Connector
- Premium composite sentiment snapshot. Aggregates Crypto Fear and Greed Index (alternative.me), VIX volatility index (Finnhub), trending ticker mentions across Hacker News top 30 + Reddit r/CryptoCurrency / r/wallstreetbets / r/stocks hot posts with per-headline keyword-based sentiment scoring, and top Polymarket prediction-market signals. Output includes per-ticker mention_count_24h, sentiment_score (-1 to +1), sentiment_label, and sample headlines. Use to gauge market mood before a trading or research decision. Costs 2 credits ($0.04 USDC). Requires Authorization: Bearer tf_live_<64-char-hex>. The notes field documents that scoring is keyword-based (crude but signal-bearing), not LLM-derived; treat as one input to a broader analysis.Connector
- P13 — list every channel ChiefLab can ship to (LinkedIn / X / Threads / Bluesky / Instagram / Facebook / TikTok / Product Hunt / Hacker News / Reddit / Discord / Slack / Indie Hackers / DEV.to / YC Bookface / email / blog / GA4 / Search Console / Stripe). Returns the catalog grouped by category (social / community / email / blog / analytics) with each channel's capabilities (publish / schedule / read_metrics / connect / fallback) and providers. USE WHEN the user asks 'what channels can ChiefLab post to?', 'which platforms are supported?', or before calling chiefmo_launch_product to pick the right channels.Connector
- USE WHEN a launch action is blocked because the channel has no automated publish path (Product Hunt, Hacker News, Reddit, Discord, Slack communities). Returns a paste-ready manual-publish brief: the exact text to post, a per-platform checklist (best time, tags/flair, who to ping, first-comment script), the URL the user pastes back to ChiefLab once posted, and a measurement template the agent can call 24h later via chiefmo_record_proof. Converts a 'blocked' channel into a 5-minute human-in-the-loop ship. Approval-gated upstream: the originating publishAction must already be 'approved' on the reviewUrl before this tool returns the brief.Connector
- USE WHEN a launch action is blocked because the channel has no automated publish path (Product Hunt, Hacker News, Reddit, Discord, Slack communities). Returns a paste-ready manual-publish brief: the exact text to post, a per-platform checklist (best time, tags/flair, who to ping, first-comment script), the URL the user pastes back to ChiefLab once posted, and a measurement template the agent can call 24h later via chiefmo_record_proof. Converts a 'blocked' channel into a 5-minute human-in-the-loop ship. Approval-gated upstream: the originating publishAction must already be 'approved' on the reviewUrl before this tool returns the brief.Connector