Spec Driven Development
by formulahendry
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Runs on your computer★ 440MITUpdated 14 months ago
Install
vulntel
Overview
Description from the maker (original English)
Free hosted CVE intel for bug-bounty agents: CVE fact-check, attack approaches from paid H1 reports
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi3 of 3 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs in the cloud
- Transport: Streamable HTTP
- Category: Other
- You need to fill in: Authorization
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 3 of 3 passed
- Runs on the maker’s server: what you ask it goes through their server.
- Can do 13 things (tools) enrich_cve, check_technology, hunt_plan, observe …
- You fill in yourself:
Authorization
Values marked secret are keys to your account. Never share them or paste them into a chat.
You need
- Runs in the cloudNothing to install; it connects over the internet
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
Run this in your terminal
claude mcp add --transport http vulntel https://mcp.vulntel.com/mcp --header 'Authorization: your-value'Fill in the empty values before running it.
Or copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"vulntel": {
"url": "https://mcp.vulntel.com/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"vulntel": {
"type": "http",
"url": "https://mcp.vulntel.com/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
Your choice stays on this device in a cookie; no account needed.
Values you fill in
Authorizationsecret HTTP headerOptional bearer token. Without one, nine of the 13 tools run 25 times a day per network (the answers say how many calls are left). A free key from https://vulntel.com/signup lifts that to 60 calls a…
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Tool names and descriptions exactly as the server reported them on Nov 6, 2026. The maker wrote them, not us; we show them as plain text.
enrich_cveFull intelligence for a single CVE: CVSS, KEV status, EPSS, CISA SSVC (exploitation/automatable/technical_impact), P1-P4 priority with rationale, affected products/versions, Debian/Ubuntu/Alpine fixed builds per release (`distro_fixes`), and (live) public-exploit signal. Args: cv
check_technologyFind vulnerabilities affecting a product across NVD (CPE) and OSV (package ecosystems), de-duplicated and ranked by priority/EPSS/CVSS. Distinct products that share a name are kept distinct. If one name maps to several VENDORS' unrelated products (e.g. "Sentry" → sentry, mobileir
hunt_planTurn a recon'd stack into a ranked dig-order for authorized bug-hunting. For each discovered component, returns its top high-risk CVEs (KEV / CISA-SSVC- active / high-EPSS first) AND its `recurring_loci` — the bug classes (CWE) this product family repeatedly fails at, ranked by r
observeScan a host's exposed stack and join it to the CVE corpus — the recon workhorse. Fingerprints the homepage + JS bundles (recovering the backend identity and API endpoints homepage detection misses on SPAs), then ranks against live KEV / SSVC-active / high-EPSS into a dig-order. F
search_vulnsSearch the CVE corpus — one entry point, three retrieval modes picked from your arguments: - query= a concept / technique / weakness (e.g. "SSO SAML assertion replay", "deserialization gadget chain", "server-side request forgery cloud metadata"). By default it FUSES full-text key
find_attack_approachesFind how bugs *like this* were actually FOUND — retrieve real disclosed bug-bounty report mechanic-cards whose approach is closest (by mechanism) to your query or a seed CVE. The "what approach worked on a bug like this, on which program, and what did it pay" layer: grounded in r
find_continuationsWhen you're STUCK mid-hunt: describe your POSITION — the attacker state/capabilities you hold, stripped of product names — and get the CONTINUATIONS that worked from positions like it, matched against the full disclosed-report BODIES (the concrete step/payload/precondition), not
assist_submissionSubmission & escalation co-pilot for a bug-bounty finding. Paste your DRAFT finding (and what you already tried / couldn't achieve) and get a grounded brief built from the closest REAL disclosed reports: (1) precedent & validity — is this an accepted class, with citable reports (
program_outcome_priorAt the START of an engagement on a bug-bounty PROGRAM, get a grounded prior over what bug classes have historically LANDED there — to decide what to look at first and what to skip. Built from real HackerOne disclosed reports: the class distribution for this program, each with LIF
new_in_scopeFind FRESH attack surface: bounty-eligible assets that entered a public bug-bounty program's scope in the last `days` (HackerOne, Bugcrowd, Intigriti, YesWeHack, mirrored daily), the least-hunted surface there is. Raw scope additions are mostly not new (in one week 57 of 80 were
verify_cve_claimFact-check a claim about a CVE against the corpus — catch hallucinations before they ship. Verifies: does the CVE exist; does it affect the claimed product at the claimed version; is the severity right; is it actually KEV-exploited. Returns per-assertion verdicts (supported / ref
corpus_statsCorpus size and data freshness (CVE / KEV / EPSS counts and latest timestamps).
search_public_codeSearch public repositories for an exact code string; return WHERE it appears. Use it to hunt vendored / copy-pasted copies of known-vulnerable code: search a distinctive line or symbol from the vulnerable function, then FETCH AND READ the hits to judge which copies are still unpa
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified against the domain vulntel.com (the registry checks domain ownership)
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- ✓ Pass
Endpoint responds
Responded in 93 ms (HTTP 200)
- – Not applicable
Sign-in with OAuth
No sign-in needed
- ✓ Pass
No hidden instructions in tool descriptions
Read 13 tool descriptions and found no hidden instructions to the AI
Compared with others in Otheri
- More stars than 0% of the other 32623 servers in this category
- Published to the registry more recently than 90% of the other 32623 servers in this category
- Basic checks equal to or better than 100% of the other 32623 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is vulntel safe?
It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
You need to fill in: Authorization
Does it run on my computer or in the cloud?
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
Is it still maintained?
The GitHub repo last changed –, and the latest version (1.2.0) reached the registry 3 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
What can I use instead?
In the same category: Spec Driven Development, Remote Desktop Commander, Draugr
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Remote Desktop Commander
by desktop-commander
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Runs in the cloud★ 211Updated 2 days ago
Install
Draugr
by draugr-dev
Security scanning for AI agents: SAST, SCA, secrets, IaC, DAST, ranked by real risk.
Runs on your computerUpdated today
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
vulntel
Most CVE tools hand your agent raw data. This one ranks it by what's actually being exploited, finds bugs by mechanism, catches the CVEs your agent invents — and transfers attack mechanics from ~14,000 disclosed bug-bounty reports.
A curated, hosted MCP corpus: ~422,000 CVEs, fused from NVD + CISA KEV + FIRST EPSS + OSV/GHSA + CISA Vulnrichment (SSVC), plus a mechanic layer distilled from ~14,000 disclosed, paid bug-bounty reports — refreshed daily. Not another live-API wrapper.
Free. Try it with no key (nine tools, 25 calls a day per IP address), then get a key: enter your email and your personal key is sent over. Tell me what you are hunting.
Why this, and not the next CVE wrapper
Most CVE MCP servers are thin wrappers: at query time they fan out to the same free public APIs and hand back whatever comes out. This is different in six concrete ways.
- A curated, embedded corpus, not a live proxy. One record per vulnerability, fused across NVD, OSV/GHSA and KEV through an identity graph, with roughly 2,100 vendor-qualified product aliases and embeddings for semantic search. Queried locally, ranked consistently.
- SSVC as priority, not just CVSS. Priority is exploitation-first: CISA SSVC (active / automatable / total impact), KEV and EPSS drive a P1 to P4 ranking. The wrapper MCPs do not carry SSVC at all.
- Search by mechanism, not keywords. Semantic search finds the same bug *class* across different products. Keyword tools structurally cannot.
- It fact-checks the agent.
verify_cve_claimcatches invented CVEs and wrong attributes. This is the one that matters most right now, with hallucinated AI bug reports flooding triage, and effectively no other CVE MCP does it. - Backport-aware. Paste a server banner (
OpenSSH_8.9p1 Ubuntu-3ubuntu0.10,Apache/2.4.62 (Debian)) and each CVE carries the Debian / Ubuntu / Alpine tracker's verdict for that exact build next to the upstream one. Upstream-only tools call a patched distro host vulnerable. - Right vendor, and no false zeros. "GitHub Enterprise" resolves to the right vendor, not every product that ships an "enterprise_server." A product it cannot resolve returns
resolved: falsewith suggestions, never a silent0that reads as "not affected." A false zero is the worst answer a security tool can give.
The hard part of AI-assisted security is not *finding* CVEs. It is triage, prioritization, and false positives. That is what this targets.
Everything below is real output from the live server, trimmed only for length.
It fact-checks your agent
The differentiator that matters most. Your agent cites CVE-2025-99999:
verify_cve_claim("CVE-2025-99999")-> exists: false "No record in NVD / OSV / GHSA. Likely hallucinated or not-yet-published."
Or it gets the details wrong. Claim: *"CVE-2021-44228 is a medium-severity Apache Struts bug, and it is not exploited."*
verify_cve_claim("CVE-2021-44228", product="Apache Struts", severity="medium", exploited=false)refuted "not exploited" -> in CISA KEV (added 2021-12-10) refuted "severity medium" -> actual CVSS 10.0, P1 refuted "affects Apache Struts" -> no product matching "Apache Struts"
The other feeds hand your agent data. This one tells you when the agent is wrong, before it reaches a report.
Priority is exploitation-first (SSVC, KEV, EPSS), not CVSS
check_technology("GitLab") returns 792 CVEs for the product, de-duped and ranked so the exploited ones float to the top:
P1 KEV EPSS 99.8 CVE-2023-7028 account-takeover: password-reset email sent to an attacker address (CVSS 10)P2 KEV EPSS 98.5 CVE-2021-39935 unauthenticated SSRF via the CI Lint API P3 EPSS 99.7 CVE-2023-2825 unauthenticated path traversal, arbitrary file read (CVSS 10) P3 EPSS 99.7 CVE-2022-2992 authenticated RCE via the GitHub import API (CVSS 9.9)
Names that map to more than one vendor are flagged ambiguous (here, gitlab vs a jenkins plugin) and kept separate, never silently merged. enrich_cve then gives you the full SSVC picture for any one of them:
enrich_cve("CVE-2024-3400") PAN-OS GlobalProtectP1 KEV CVSS 10.0 EPSS 99.95 unauthenticated command injection -> root RCE SSVC exploitation=active automatable=yes technical_impact=total Metasploit exploit/linux/http/panos_telemetry_cmd_exec (rank: excellent) Public PoC 44 repos (h4x0r-dz 162 stars, W01fh4cker 90 stars, ...)
Turn recon into a dig-order
hunt_plan(["craftcms 4.4", "nginx", "keycloak"]) ranks your stack by its most-exploitable bug and names where each component historically bleeds:
#1 craftcms 4.4 97 CVEs, 12 high-riskrecurring_loci CWE-94 code injection x7 (2 exploited in the wild) -> probe template / eval surfaces first dig here P1 KEV EPSS 99.8 CVE-2025-32432 unauthenticated RCE (CVSS 10) your 4.4 is AFFECTED, fixed in 4.14.15 P1 KEV EPSS 99.9 CVE-2024-56145 RCE when register_argc_argv is on AFFECTED, fixed in 4.13.2
#2 nginx HTTP/2 Rapid Reset CVE-2023-44487 (KEV) #3 keycloak recurring_loci CWE-287 auth x12. OIDC request_uri SSRF CVE-2020-10770
It does not just list CVEs. It names the bug *class* a product family keeps failing at, ranked by real exploitation, and tells you whether *your version* is in range. Where to look, and what shape to expect.
Search by mechanism, across products
search_vulns(cve_id="CVE-2021-44228"), "what else works like Log4Shell":
sim 0.88 CVE-2021-44832 Log4j2 JDBC Appender, JNDI LDAP RCEsim 0.82 CVE-2022-40145 Apache Karaf, code injection via an attacker-controlled JNDI URL sim 0.79 CVE-2022-34916 Apache Flume, JNDI LDAP RCE via a JMS source
The same JNDI-injection mechanism, surfaced across *different products*. A keyword search for "log4j" never finds Karaf or Flume. Or search a concept directly, search_vulns("SAML SSO authentication bypass"):
P3 CVSS 9.1 CVE-2024-9487 GitHub Enterprise: SAML SSO bypass via signature verificationP3 CVSS 9.8 CVE-2025-25291 ruby-saml: auth bypass via a ReXML / Nokogiri parser differential P1 KEV CVSS 9.8 CVE-2025-59718 Fortinet FortiOS / FortiProxy: signature-verification bypass
See what is being exploited right now
search_vulns(days=7), run live today:
P1 KEV CVSS 10.0 CVE-2026-10520 Ivanti Sentry: unauthenticated OS command injection -> root RCEP1 KEV CVSS 9.3 CVE-2026-50751 Check Point: IKEv1 auth bypass, remote-access VPN without a password P2 KEV CVSS 8.8 CVE-2026-11645 Chrome V8: out-of-bounds read/write -> sandbox escape RCE
Median time from disclosure to in-the-wild exploitation is now days, not months. The Ivanti bug above carried a CISA remediation deadline in the same week it landed. corpus_stats on 2026-11-03: ~422,800 CVEs, ~1,770 KEV entries, data under a day old. These figures are point-in-time and drift daily, so call corpus_stats yourself for the live count rather than trusting the numbers on this page.
Transfer attack mechanics from disclosed bug-bounty reports
Beyond CVEs, the corpus distills ~14,000 disclosed, paid HackerOne reports into product-agnostic *attack mechanics* — each bug's source → sink → trigger → preconditions, de-anchored from the product it was filed against. The premise: a vulnerability is a transferable mechanism, not a property of one product — so a move that paid on one stack is a checklist item on the next.
find_attack_approaches(query="ssrf reaching cloud metadata") — the human moves that transferred, novelty-ranked, each tagged with live program-actionability:
Reddit SSRF preview_url fetches an unfiltered URL → returns metadata program_active, paysU.S. DoD SSRF /download-url?url= fetches AWS instance metadata program_active Concrete CMS SSRF DNS-rebind bypass → AWS IAM creds from the metadata svc program_active
find_continuations(position=...)— matches your *accumulated attacker position* mid-hunt to the next moves real reports played from a similar spot. Every move isstatus: UNVERIFIEDwith adecisive_checkto run on the target — a legal move, never a confirmed bug.assist_submission(finding=...)— a grounded submission brief from the closest paid precedents (validity, what's novel, an escalation playbook), with every cited report validated against the corpus (citations_grounded) so it can't smuggle a fabricated precedent.program_outcome_prior("hackerone:gitlab")— the bug classes that historically *landed* on a program, with lift over base rate (GitLab: SSRF 3.4×, SQLi ~never).
Honest about what this is: it primes and grounds a human hunter — it surfaces the move and the precedent. It does not find the bug for you; the target decides whether the move survives, and that's a step you still run.
The whole point: a memory of mechanics to borrow and run — not a CVE lookup
The moat is three things a stateless model cannot self-generate, and this corpus holds all three:
- Watched over time — priors, temporal drift (Log4Shell's affected set kept growing +1,200 days after publish), score stability. Your model has a training-cutoff snapshot; this has the *trajectory*.
- Seen many — every disclosed mechanic and CVE mechanism, embedded, so the *same bug class* transfers across products a model would never connect: Log4Shell's JNDI lookup → Apache Karaf, Flume; an SSRF that paid on Reddit → the move to try on the next target.
- Live-fused recon —
observerecovers a host's real backend from its JS bundles and joins it to the corpus on the spot.
The cardinal sin is treating it as a severity-number checker. The job is to transfer a proven mechanic onto your target and run it — or read a fix to *falsify* an option before you spend a probe on it.
Force your agent to reach for it — it won't on its own
Left alone, an agent answers from training data: stale, and it *invents* CVE ids under pressure. Paste this operating loop into your agent's rules (CLAUDE.md, Cursor/Windsurf, a system prompt):
You have the vulntel MCP. Your own CVE knowledge is a guess to be verified — prefer the corpus.Operating loop, in order:
- Choosing / scoping a bounty program → new_in_scope (what just entered a program's scope, re-adds filtered) and program_outcome_prior (which bug classes have actually PAID here).
- A live host → observe (a cache miss returns status="scanning"; call again with the same host until "ready"). Mine endpoints[], recurring_loci, the CVE join, not just two fields.
- A product + version → check_technology / hunt_plan (dig-order + the recurring CWE loci).
- Before asserting ANY CVE / "affects X" / "severity Y" / "exploited" → verify_cve_claim. Never cite from memory.
- Feasibility of one CVE → enrich_cve; read the MECHANISM (POST vs GET, auth-required) to judge whether it chains. How it was fixed in the wild, or who vendored the vulnerable line → search_public_code (raw hits; read them).
- Hunting a class → find_attack_approaches for the transferable move; RUN it on the target, don't cite it. Loop with a growing tried=.
- Stuck / messy position → find_continuations(position) for the by-step move; then search_vulns that class to see whether it recurs in this stack.
- Submitting → assist_submission; EXECUTE the techniques it transfers (referrer differential, key-reuse breadth), then file.
- Before trusting a "nothing found" → corpus_stats (corpus size and
Only the beginning is shown; read the rest in the repo