MCP.Market

OmniSeek MCP server

by Battam1111·io.github.Battam1111/omniseek·v0.2.1·69 stars

Your agent seeks what search can't find. A self-hosted perception MCP server.

A92/100grade A
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Safety scan
A92/100

full report

Adoption
Growing

69 stars55 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

OmniSeek tools (19, 1 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • _set_limiter
  • omniseek_coauthors

    Use WHEN you want WHO a researcher collaborates with — advisor + closest collaborators by joint-paper count, or how a paper's author group is connected (WebSearch cannot build this). One LAYER, not the whole graph — co-authorship is one edge type; YOU overlay the others (advising, institution cohort, citation, code, social) and judge what each connection MEANS.

  • omniseek_curator_act
  • omniseek_curator_view

    Use WHEN running the source-curation protocol (judge the admission queue or a source audit) — READ curator state: queue | packet | audit. Never mutates. Pick a view with ``what``:

  • omniseek_field_skeleton
  • omniseek_gatherwrite action

    Run N independent read-only eye tools IN PARALLEL, returning results in one response.

  • omniseek_graph
  • omniseek_institution_cohort

    Use WHEN you need the people-ROSTER of a lab / department / university (who actively publishes there, optionally scoped to a field) — the "who's at this lab" question, orthogonal to co-authorship ("same lab, never co-authored" is still a tie, and the people-roster of a target lab is exactly the SG/Canada cohort question).

  • omniseek_paper_enrich

    Use WHEN you need ONE paper's open-access full-text PDF, retraction / integrity status, or citation count — signals omniseek_search / field_skeleton do NOT give cleanly. Keyless, mechanical: YOU decide when + on which papers.

  • omniseek_paper_recommend

    Use WHEN you have a paper and want more like it — semantically-similar papers (SPECTER embeddings) that keyword search and the citation graph miss, including very recent work. Uses Semantic Scholar's recommendation model (SPECTER embeddings + co-citation), so it surfaces conceptually-related work that omniseek_search (keyword) and omniseek_field_skeleton (citations) miss — including very recent pa

  • omniseek_read
  • omniseek_resolve_identity

    Resolve a PERSON's name to candidate author ids — the shared front door for EVERY relationship layer (you must know WHICH person before you can map their connections).

  • omniseek_ruling

    Use WHEN two graph nodes ARE (or are NOT) the same person / entity and you want views to collapse them — record / list / retract same_as | not_same_as rulings (the one judgment channel the graph's working policy applies).

  • omniseek_search
  • omniseek_sensor

    Use WHEN you want to MONITOR a query over time and be told only what's NEW — standing queries with novelty detection. ONE verb; ``action`` picks what to do.

  • omniseek_sources
  • omniseek_statement
  • omniseek_transcribe
  • omniseek_view

Public scan report

scanner v0.1.10 · 2026-10-03 · same rubric, same numbers if you re-run it

no findings
  • Code scan220 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 0 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 92/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How OmniSeek compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
92/100
higher than 90% of 4,460 AI and agents servers
Tools
19
the typical AI and agents server has 6
Tools that change things
5%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
69
more than 93% of 2,711 AI and agents servers
Downloads a week
55
more than 46% of 1,538 AI and agents servers with a package

What its tools let an agent do: 18 read · 1 change

Install OmniSeek in Claude Code, Cursor or VS Code

claude mcp add omniseek -- uvx omniseek
Add to Cursor

What the publisher says

From the OmniSeek repository's README, as published. We do not edit it. Read it on GitHub

<!-- mcp-name: io.github.Battam1111/omniseek -->

The answer is sitting in minute 47 of a podcast, three replies deep in a comment thread, behind a login, in another language. Your agent gets it anyway.

Self-hosted perception MCP server · one connection

&nbsp; &nbsp; &nbsp; &nbsp;

Quick start · Tools · Configure · Contributing

Languages: English · 中文 · 日本語

Search gives your agent indexed pages, in one language, in text, and stops there.

OmniSeek gives it the senses to keep going: through languages, logins, comment threads, audio, and pixels, all on your machine.

What each layer gave back, verbatim:

  • Written down, and in reach. Headlines, official FAQ, top blogs, all one voice: "From 2026, F-1 admission is limited to a 4-year initial period; renewal in a third country remains possible." All quote the same rule. None of them have done it.
  • Written down, but out of reach. Three first-person threads on 1point3acres, behind your own login: Bangkok, booked to passport in 25 days, interview to approval in 30 minutes; Milan, a month-long fight for a slot, visa issued for 5 years; Tokyo, "silky-smooth". Under the Milan post the author comes back in the comments: "Book any late slot first, then email the consulate to expedite. For one F-1 applicant it worked." One person's experience, not official guidance.
  • Never written down. A Chinese explainer video on bilibili, transcribed locally: the "4-year cap" in the headlines is the initial period, extensions moved desks rather than vanishing. A rednote video note whose caption is four hashtags, frames and speech read locally: a 212(a)(6)(C) refusal abroad, a misrepresentation finding, can nearly close the F-1 road.

Plain search quoted the rule and stopped. The people who had lived it held the timelines, the workaround, and the risk. OmniSeek also named the sources it held back, each with the exact call to drill it.

It hears (local bilingual ASR, no cloud), sees (images and video frames, in-band), crosses languages (a Chinese query finds English results and vice versa), reads behind login walls (your credentials, your machine, off by default), and remembers (persistent retrieval memory plus a typed, source-traced evidence graph).

Crossing languages draws on the index OmniSeek builds as you use it, so a fresh install starts at a floor. The published claim-verification tests run on exactly that fresh install, which makes their cross-lingual number the coldest case rather than the typical one.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

OmniSeek: common questions

Is OmniSeek MCP server safe?
Yes, by our scan: it is graded A (92/100). Read the OmniSeek safety report
How do I install OmniSeek?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does OmniSeek need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is OmniSeek maintained?
The last commit was 32 days ago (2026-10-03). The latest release is v0.2.1.
What can I use instead of OmniSeek?
Servers from other publishers that do the same job: SuperCompress MCP server, Agent Sniper MCP server and Mnemoverse Memory MCP server.
How does OmniSeek compare with other AI and agents MCP servers?
safety score 92/100 (higher than 90% of 4,460 AI and agents servers); tools 19 (the typical AI and agents server has 6); tools that change things 5% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to OmniSeek

Same job from other publishers: the closest match first, then the best rated.

  • SuperCompress
    Compress coding-agent context ~64%. Hosted Neural Keep MCP for Cursor/Claude/Codex.
    B
  • Agent Sniper
    Self-custodial pump.fun sniper: arm strategies, snipe, manage positions. Simulate by default.
    B
  • Mnemoverse Memory
    Hosted agent memory that learns from outcomes, with shared rooms. No key: mcp.mnemoverse.com/mcp
    A