u/the_mine_works

Most job-data MCP servers I've come across are US-first, so I built one for India. Nine boards (Naukri, Indeed India, Foundit, Shine, Apna, CutShort, Hirist, Instahyre, Internshala), plus LinkedIn candidate sourcing and AmbitionBox employer snapshots. 14 tools on one remote endpoint, no install step.

The design question I spent longest on, and the part I think is actually worth discussing: whether to expose nine separate search tools or one.

I ended up shipping both, for a reason I didn't anticipate. Nine individual tools (search_jobs_naukri, search_jobs_apna and so on) alongside a search_all_india_jobs that fans out across them. Agents genuinely use them differently. Ask "find Python jobs in Bangalore" and the agent reaches for the composite and gets one merged deduped list. Ask "what's on Naukri right now" and it picks the single board. Forcing either pattern on its own made things worse, either fanning out expensively to answer a question about one board, or making nine calls where one would have done.

What I got wrong first time round: the composite returned everything in a single payload. On a broad query that swamps the context window and the agent starts silently dropping results, which is the worst failure mode because nothing errors. Splitting it into a partial-then-section pattern (return a summary, fetch a section on demand) fixed it, and that's why there are more billing events than tools if you go looking.

Billing is per event and a call returning nothing isn't charged, which matters more than it sounds once an agent is exploring and half its queries come back empty.

Usage so far is small but real: 12 users in the last 30 days, 55 runs total. Mostly recruiting-side workflows rather than the job-seeker side I'd expected.

https://apify.com/themineworks/india-jobs-mcp

Disclosure: I built this and it's a paid server. Happy to get into the fan-out or the billing design if useful.

Every agent I've thrown at company research does the same thing. It confidently states a CIK number, an LEI, or a court case that does not exist. Sounds right. Is not right. Turns out "grounding" an agent just means pointing it at the actual government database instead of hoping the training data got it right.

So I built an MCP server that wraps 13 official sources: SEC EDGAR, GLEIF, US state business registries, CourtListener, USAspending, FEC, UK Companies House, EU VIES, and a few more. One call resolves a company's real legal identity, another pulls its actual filings, another checks if anyone is suing it.

Real example, not a cherry-picked demo: asked it who runs Tesla's Connecticut entity. Came back with the registered agent, the exact incorporation date, and the two officers on file, sourced straight from Connecticut's own registry, with a link to prove it. It can't invent a name because it is reading a government API, not guessing.

Honest limits, since rule 2 exists for a reason: state registry coverage is thin right now (New York, Colorado, Connecticut, Oregon, that's it). Delaware has no public API at all, so if that's your use case this will let you down gently. US and EU data is solid. Everywhere else, thinner.

Runs on Apify, pay per successful call, and it charges nothing on an empty result. Built it on top of scrapers I already run there. Happy to take a beating on the design in the comments if anyone has opinions.

https://apify.com/themineworks/company-diligence-mcp