Fetch Codeforces problem metadata, tags, and contest limits by providing a contest ID and problem letter.
MIT
524,441 tools. Updated 2026-09-06 15:49
"Codeforces" matching MCP tools:
- Search Codeforces problems by rating range and tags, optionally excluding ones a handle has already solved to find fresh practice targets.-
- Rank a Codeforces user's problem tags by solve rate, weakest first, to identify practice gaps using deduplicated submission history.-
- Retrieve a Codeforces user's recent submissions, filterable by verdict, with direct links to each submission for code review.-
- Retrieve a Codeforces user's rating, max rating, rank, and organization by handle to evaluate their competitive standing.-
- Search Codeforces problems by rating range and tags, with OR/AND topic matching, and sort by recent or oldest. Returns up to 10 problems with names, ratings, tags, and links.MIT
Matching MCP Servers
- FlicenseAqualityBmaintenanceEnables coding agents to discover unsolved Codeforces practice problems, analyze tag performance, and inspect submissions, profiles, rating history, and upcoming contests through MCP-compatible clients.6-
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to access Codeforces public data (users, contests, problems, etc.) via natural language or direct tool calls through Pipeworx gateway.16MIT
Matching MCP Connectors
Codeforces competitive programming users, contests, problems
Search Codeforces problems and inspect public problem metadata through the official Codeforces API.
- Fetch the full problem statement, rating, and topics for a Codeforces problem using its contest ID and index.MIT
- Selects a random Codeforces problem within ±300 rating of your current rating, ignoring weaknesses for a fresh and challenging practice.MIT
- Analyzes your solved Codeforces problems to identify weak topics and recommends up to 3 practice problems within +300 of your rating.MIT
- Fetch a Codeforces user's complete profile including rating, contests, problems solved, and top categories.MIT
- Retrieve a Codeforces user's last 1000 submissions to see AC/WA/TLE counts and details of their 20 most recent attempts.MIT
- Analyzes your last 10 rated Codeforces contests and recommends up to 2 unsolved problems per contest, based on rating constraints, to help you improve your rank.MIT
- Compare two Codeforces users side-by-side to analyze ratings, titles, contest count, and problem solving breakdown by difficulty and category.MIT
- Retrieve upcoming Codeforces contests with start times and durations, sorted by soonest, with options for limit and markdown or JSON output.-
- Retrieve a Codeforces user's rating history with contest-by-contest changes and deltas, oldest first, plus an optional limit for recent contests.-
- Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.ConnectorNo auth
- Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.ConnectorNo auth
- "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.ConnectorNo auth
- Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).ConnectorNo auth
- ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,798 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).ConnectorNo auth
- "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.ConnectorNo auth