First-party Indian-markets data wired to Claude Code as one MCP server. XBRL fundamentals from NSE back to FY17, 23,000 concall transcripts with cited Q&A, twenty years of AMFI mutual fund NAV, prices for delisted companies too. Every answer carries the source URL. 200ms per call.
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Last probed Nov 3, 2026 · genka.dev
30tools discovered
For AI agents — MCPBundles Directory API
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MCP connect URL: https://genka.dev/mcp
Skill page: https://www.mcpbundles.com/skills/genka-mcp-e1bdd4fbd9
Explore capabilities (30)
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Mf8
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Other capabilities4
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Federated entity search across funds, listed companies, sectors, and themes. Returns grouped results with slugs/symbols you can pass to *_get tools. Use this BEFORE any *_get when you only know a name. 5 credits.
Search across the API — Federated entity search across funds, listed companies, sectors, and themes. Returns grouped results with slugs/symbols you can pass to *_get tools. Use this BEFORE any *_get when you only know a name. 5 credits.
Discover what's queryable — ONE-shot orientation: every queryable dimension across funds + stocks + concalls + sectors. Returns metric names, filter ops, periods, themes, AMCs, sectors, benchmarks, snapshot date ranges, return windows, indicators, pricing tiers. Call this on session start. Free.
Dataset freshness heartbeat — Counts + latest dates across funds/NAVs/metrics/prices/filings/concalls. Use to check if data is stale before relying on it. Free.
Bulk dataset export — Bulk export of a dataset as JSONL/CSV (parquet currently routes through JSONL bytes). Use for downstream backtests or analysis. 50 credits.
Fund detail — Single fund detail: AMC, SEBI category, theme, canonical scheme code, expense ratio, AUM, benchmark, status (active|closed|halted). Always check `status` before recommending a fund -- many international funds are closed to new subscriptions. 1 credit.
Fund risk metrics — Risk metrics for a fund. Returns absolute + rolling distributions for cagr, vol, sharpe, sortino, max_dd, ulcer, upi, calmar, plus benchmark group (alpha, beta, tracking_error) and tail_risk (var_95, cvar_95, skew, kurt). Time-travel via as_of. 1 credit.
Fund holdings — Top holdings of a fund with weights. Each holding carries `asset_class` (Equity, Debt, FoF, Cash) and `ticker` (NSE symbol when listed; null for foreign / cash positions like TREPS). To answer 'top equity holdings' filter client-side on asset_class=='Equity' AND ticker is non-null. Coverage is uneven -- PPFAS has monthly snapshots, Tickertape covers ~2,100 funds with one snapshot, ~2,600 have nothing. Always check `count` and `as_of`. 1 credit.
Pairwise holdings overlap — Pairwise holdings overlap between two funds. Returns shared constituents, weight overlap %, concentration differential. Use when deciding 'do these funds duplicate each other?' before adding both to a portfolio. 5 credits.
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A working endpoint is step one. Directory coverage is the coordinated launch across ChatGPT, Claude, Cursor, the MCP Registry, and community indexes.
What is the Genka — Indian markets API for agent use MCP server?
First-party Indian-markets data wired to Claude Code as one MCP server. XBRL fundamentals from NSE back to FY17, 23,000 concall transcripts with cited Q&A, twenty years of AMFI mutual fund NAV, prices for delisted companies too. Every answer carries the source URL. 200ms per call.
How do I connect Genka — Indian markets API for agent use to my AI agent?
Use the MCP endpoint listed on this page in your MCP client configuration. One-click install pills support Claude, Cursor, VS Code, and other hosts. Copy the remote MCP URL if your client needs a manual entry.
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Filter the MF universe — Filter funds by any metric column. Filter param convention: {metric}_{absolute|rolling_<stat>}_{op}=value, e.g. sharpe_absolute_gte=1.0. Sort: -col for descending. Filter by category/theme/factor/amc as enums. Call `capabilities` first to learn the full grammar. 5 credits.
Compare 2-6 funds head-to-head — Aligned NAV + metric matrix for 2-6 funds. Returns rebased-to-100 series for chart-ready output and side-by-side metric tables. 5 credits.
Backtest a fund portfolio — Multi-fund portfolio backtest. Buys at `from`, rebalances at the chosen cadence (none|monthly|quarterly|annual) until `to`. Returns CAGR, vol, Sharpe, max_dd, total_return, monthly returns. Survivorship-transparent (echoes inactive_funds_used). 25 credits.
Simulate a monthly SIP — Monthly SIP simulation. Buys monthly_amount worth of units on the first trading day of each calendar month between from and to and values the position at the latest NAV. Returns total_invested, current_value, units, absolute_return, XIRR. 25 credits.
Company detail — Listed company profile (NSE). Optional `expand` pulls in: ratios (latest quarter snapshot), recent (52w hi/lo + DMA50/200 + RSI14 + MACD + 1y/3y/5y returns), corp_actions (recent splits/bonuses/dividends), filings (recent XBRL annuals). For ratio TIME-SERIES or filtering by single metric, use `co_ratios` instead -- expand:[ratios] only returns the latest snapshot. 1 credit.
Quarterly ratios time-series — Quarterly valuation/quality ratios for a company: pe, p_b, p_s, ev_ebitda, roe, roce, mcap_cr, ev_cr, revenue_ttm, pat_ttm, ebitda_ttm. Filter by metric or date range. Coverage from FY2017 (NSE XBRL universal mandate). 1 credit.
Income / balance / cash-flow statements — Quarterly or annual XBRL financial statements. Pick `type` = income | balance | cash_flow. Coverage from FY2017. 1 credit.
Filter the listed-company universe — Filter listed companies by financial ratios and industry. POST-style filter spec: each filter is a {op, value} pair. Ops: gte | gt | lte | lt | eq | between (value=[min,max]). Numeric columns include pe, p_b, p_s, ev_ebitda, roe, roce, mcap_cr, ev_cr, revenue_ttm, pat_ttm, ebitda_ttm, return_1y, return_3y, return_5y, return_1y_tr. Industry is the literal NSE industry name (e.g. 'Information Technology', 'Financial Services', 'Capital Goods') -- not a slug. 5 credits.
Bulk close prices for a portfolio — Close prices (or OHLCV via metrics) for many symbols at once. Use for portfolio-level valuation or correlation analysis. 5 credits.
OHLCV bars for one symbol — Daily OHLCV bars for a single symbol over a date range. Use for charting or backtesting. Bhavcopy goes back to 1995-01-02; daily refresh at ~13:45 UTC. 1 credit.
Latest snapshot + indicators — Latest snapshot for one symbol with pre-computed indicators: 52w hi/lo, all-time hi/lo, DMA50/200, RSI14, MACD, Bollinger, ATR14, return_1d/1w/1m/3m/6m/1y/3y/5y/si in three flavours (raw, split-adj, total-return). Optionally expand into bars or corp_actions. 1 credit.
Search earnings-call transcripts + investor presentations + DRHPs — Find passages matching a query across the 18K+ doc corpus (8y of NSE 500 transcripts, IP slide decks, NSE-side dual filings, DRHP/RHP/LOF prospectuses). Returns hits with id (use concall_get to fetch full doc) plus kw_hits + tf + days_old breakdown so the score is interpretable. Score formula: (kw_hits/N) * (1 + 0.3 * tf_density) / (1 + days_old/365). 5 credits.
RAG answer over the concall corpus — Synthesized answer to a natural-language question, grounded in earnings-call transcripts. Returns answer text + citations[] with [N] markers tied to fragment ids. Use this instead of concall_search when the user asks a question (vs. searches a phrase). LLM tier, ~1.2x upstream cost.
Full earnings-call transcript — Fetch the full transcript by id (from concall_search hit ids or concall_answer citations). Use sparingly -- payloads can be 30k+ tokens. 1 credit.
Funds holding a stock, ranked by exposure — List MFs that hold a given NSE-listed stock, ranked by exposure_cr (= weight_pct/100 * AUM, the actual rupee commitment). A 6% weight in a 60,000cr fund is a bigger position than a 23% weight in a 200cr index fund -- this ranks accordingly. Returns aggregate (n_funds, total exposure, max weight) plus per-fund rows. 1 credit.
One-shot smart-money summary for a stock — Total institutional MF ownership of one stock: n_funds, total_exposure_cr, max single-fund weight, AUM-weighted average weight, top-5 holders inline, sector context. Use this when you want 'how much MF money is in TCS?' in a single call. Use holdings_by_stock for the full per-fund list. 1 credit.
MFs ranked by exposure to a sector — Rank every active MF by total weight + INR exposure to a given NSE industry sector. Useful for 'find me the most IT-heavy flexi-cap fund' or 'which AMC is overweight financials?'. Slug is kebab-case of NSE industry name -- discover via /latest/capabilities (companies.sectors). 1 credit.
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