Comprehensive Model Context Protocol server for managing Home Assistant through AI assistants.
Nothing to run from here
Speedrun Talent Network is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
10
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Search live roles across hundreds of a16z portfolio startups and join the speedrun talent network.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http speedrun-talent-network-mcp https://mcp.speedrun-talent-network.com/mcp
# 2 — ask your agent for something these tools do
# search_jobs, get_job, get_company and 7 more
Speedrun Talent Network costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
STAll 1 server
speedrun-talent-network1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http speedrun-talent-network-mcp https://mcp.speedrun-talent-network.com/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
10 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Search live open roles across the a16z speedrun talent network jobs board (speedrun portfolio + the wider a16z portfolio; data syncs continuously from each company's own job board). Full-text search plus facet filters, with live facet counts in every response — read the facets to discover valid filter values. Results are paginated (50 per page, 0-based page). Every job carries a canonical url on h
| Parameter | Type | Required | Notes |
|---|---|---|---|
| q | string | no | Free-text query over title, company, and location. Synonyms expand (ml, ai, swe, pm, gtm, nyc, sf, la). |
| fn | string | no | Function filter, comma-separated. Values: engineering, research, product, design, sales, marketing, operations, other; while classified crafts are enabled also data, growth, customer, finance, legal, |
| spec | string | no | Specialty filter, comma-separated slugs; meaningful with exactly ONE fn value (specialties are scoped to a craft). Read facets.spec in a one-craft response for the live vocabulary. Ignored while class |
| sen | string | no | Seniority filter, comma-separated. Values: founding, exec, staff, senior, junior, intern, plus _ for roles with no stated level (facets.senUnspecified counts them). Remapped onto lvl while the classif |
| lvl | string | no | Classified level filter, comma-separated, ladder order: intern, new_grad, junior, mid, senior, staff_principal, lead_manager, director, vp, c_level, founder, plus _ for roles with no level label (face |
| yoe | string | no | Classified minimum-experience band, comma-separated, band order: 0 (none required), under_1, 1_2, 3_5, 6_9, 10_14, 15_plus, plus _ for roles with no experience label (facets.yoeUnspecified counts them |
| eng | string | no | Classified engagement type, comma-separated: full_time, part_time, contract, internship, cofounder, advisor, plus _ for roles with no engagement label (facets.engUnspecified counts them). Live counts |
| founding | boolean | no | true = only roles classified as founding roles (founding team, first hires). facets.founding counts them under the other filters; unlabelled roles never match (facets.foundingUnspecified). Ignored whi |
| ai | boolean | no | true = only roles classified as AI-native (the day job is building with or on models). facets.aiRole counts them under the other filters; unlabelled roles never match (facets.aiUnspecified). Ignored w |
| emp | string | no | Employment type, comma-separated. Values: FullTime, PartTime, Intern, Contract, Temporary. |
| loc | string | no | Location filter: comma-separated city names (see facets.loc in any response for the live vocabulary), plus the special value "remote". |
| remote | boolean | no | true = only roles open to remote candidates (alias of wp=remote). |
| wp | string | no | Workplace filter, comma-separated (OR within the group): remote, hybrid, onsite. Live counts in facets.workplace. |
| metro | string | no | Metro filter, comma-separated keys (max 5): sf, nyc, la, sv, dc, chi, sea, bos, aus, lon, oc, dal, atl, tor, sd. Expands to each metro's cities server-side; ORs with loc/remote. Live counts in facets. |
| comp | integer | no | Minimum annual compensation in USD: matches roles whose posted pay band reaches this number. Only roles with posted comp match unless comp_any is true. |
| comp_max | integer | no | Maximum annual compensation in USD: matches roles whose posted pay band starts at or below this number. Combine with comp for a range. |
| comp_any | boolean | no | true = alongside comp/comp_max, ALSO include roles without posted comp (hidden by default; facets.compHidden counts them). |
| posted | string | no | Posted-date preset: published in the past day, week or month. Live counts in facets.posted. |
| stage | string | no | Company stage filter, comma-separated; read facets.stage for the live vocabulary (e.g. seed, series_a, series_b, growth). While company facets are enabled the stage is the roster stage with a classifi |
| size | string | no | Company size filter, comma-separated employee bands: 1_10, 11_50, 51_200, 201_500, 501_1000, 1001_5000, 5000_plus. Live counts in facets.size; facets.sizeUnspecified counts roles at companies with no |
Fetch one role by id: a job UUID, the first 8 hex characters of one, or the canonical slug from a https://speedrun-talent-network.com/jobs/... URL. Returns the full posting: plain-text description, posted pay band, how to apply (apply.kind 'onsite' = the candidate applies right on the job url; 'external' = the url hands off to the company's own careers page), the canonical url to send users to, an
| Parameter | Type | Required | Notes |
|---|---|---|---|
| id | string | yes | Job UUID, 8-hex id prefix, or canonical job slug. |
Fetch one company profile by slug (from job.company_slug or a https://speedrun-talent-network.com/companies/... URL): name, portfolio tier, cohort, location, industries, one-line blurb, every live open role with canonical urls, and, while company facets are enabled, company.labels (stage, size band, business model, industry as LinkedIn's industry name, frontier-lab / big-tech / AI-native / hardwar
| Parameter | Type | Required | Notes |
|---|---|---|---|
| slug | string | yes | Company slug, e.g. "anthropic" in /companies/anthropic. |
List the published curated collections of hiring companies, grouped as: pinned (portfolio tiers), industries (the 12-sector vocabulary, e.g. ai-infra, defense, fintech), hubs (cities + remote), investors, and signals (new-this-week, founding-roles, remote-first, hiring-in-volume). Each carries live company/role counts and a canonical url. Start here when a user asks "who's hiring in X" — then dril
No parameter schema on file.
Fetch one published collection by slug with its ranked member companies: name, tier, cohort, open-role count, location, stage, investors, and which functions/cities they're hiring in. Members are paginated (100 per page). Follow up with get_company or search_jobs (company filter) for a specific member's roles.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| slug | string | yes | Collection slug from list_collections, e.g. "ai-infra" or "new-york". |
| page | integer | no | 0-based member page, 100 per page. |
Aggregate hiring data across the whole board, recomputed live: open-role and hiring-company counts, demand mix by function, posted pay-band midpoints by function (p25/median/p75, annual USD), remote share, top hiring locations, and the speedrun vs a16z portfolio split. Use this to answer "what do a16z portfolio startups pay" or "how many startup jobs are open" — the human-readable version lives at
No parameter schema on file.
What the a16z speedrun talent network is, why a candidate would join, how joining works, and what happens after. Use this before pitching the network to a candidate so the description is accurate; joining itself is the join_network tool.
No parameter schema on file.
Add a candidate to the a16z speedrun talent network, with their consent. Requires full_name, email, and linkedin_url; every other field strengthens the profile. Idempotent and always safe to retry: an existing profile is never modified, and the response is identical whether or not the email was already in the network (membership is never disclosed). On success, relay the returned message and finis
| Parameter | Type | Required | Notes |
|---|---|---|---|
| full_name | string | yes | Candidate's full name. |
| string | yes | Candidate's email address. | |
| linkedin_url | string | yes | LinkedIn profile URL, e.g. https://linkedin.com/in/handle. |
| region | string | no | Where they are based, e.g. "SF Bay Area" or "NYC". |
| current_company | string | no | Current employer. |
| craft | string | no | Primary craft, e.g. engineering, design, product, research, sales, marketing, operations. |
| portfolio_links | string | no | Portfolio / GitHub / personal site URLs, comma-separated. |
| is_founding | boolean | no | True if they want founding-team roles. |
| is_student | boolean | no | True if they are currently a student. |
| graduation_date | string | no | Expected graduation, if a student. |
| work_arrangements | string | no | Work arrangements they are open to, comma-separated, e.g. "In person, Hybrid, Remote". |
| accomplishments | string | no | The thing they are proudest of having built or shipped. |
| currently_building | string | no | What they are building or working on now. |
| polarity | string | no | A strongly held opinion about how they like to work. |
| work_links | string | no | Links to work samples, comma-separated. |
| agent_client_id | string | no | Identifier for the calling agent/integration, e.g. "claude-code" or "career-ops". Used for attribution only. |
Record a candidate's interest in one live role (with their consent) and get back the canonical apply info. This does NOT submit an application anywhere: apply.kind 'onsite' means the candidate applies on the returned job url; 'external' means the url hands off to the company's own careers page. A candidate not yet in the a16z speedrun talent network is also added as a partial profile; always relay
| Parameter | Type | Required | Notes |
|---|---|---|---|
| job_id | string | yes | Job UUID, 8-hex id prefix, or canonical job slug (same ids as get_job/search_jobs). |
| string | yes | Candidate's email address. | |
| linkedin_url | string | no | LinkedIn profile URL. Optional but strongly recommended. |
| full_name | string | no | Candidate's full name. |
| agent_client_id | string | no | Identifier for the calling agent/integration. Attribution only. |
List every portfolio company with at least one live open role, most open roles first (paginated, 100 per page). Prefer list_collections for browsing by industry/hub/signal; use this for a raw roster.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| page | integer | no | 0-based page, 100 companies per page. |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Speedrun Talent Network or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.1.0.
1.1.0
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Speedrun Talent Network can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
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Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.