Skip to main content
Glama
510,685 tools. Updated 2026-09-04 11:18

"Finding a Programmer with MCP Certification" matching MCP tools:

  • Retrieve reference documentation for the Zaira Guide API and MCP server on demand. Topics: - getting_started — how to connect via MCP or REST, first queries - endpoints — full REST endpoint reference with parameters - mcp_tools — MCP tool reference with when-to-use guidance and a routing matrix - schema — the tool entry schema - errors — error taxonomy for REST (RFC 9457) and MCP (JSON-RPC) Call with no topic to get an index of available topics. Returns: the requested topic as a Markdown-KV block. With no topic, returns an index listing all available topics with short descriptions; call again with the relevant topic for the full content. Examples (topic selection): - "How do I call the REST API?" → {topic: "getting_started"} - "What parameters does /tools accept?" → {topic: "endpoints"} - "What fields are in a tool entry?" → {topic: "schema"} - "What error shapes do I handle, and what are the recovery steps?" → {topic: "errors"} - "Which MCP tool fits my task?" → {topic: "mcp_tools"} Edge cases: - No topic argument is valid — you get the index. This is the deferred-loading path; don't load every topic at once. - Topic must match the enum exactly (lowercase, underscore). "getting-started" with a hyphen is rejected as an unknown parameter. Risk: read-only, closed-world, idempotent — no state change possible.
    Connector
  • Authenticated — returns the caller's Blueprint learning-path state: current course slug, stage progress, certification status (Foundation, Practitioner, Capstone), Capstone track eligibility flags, and the next recommended stage. WHEN TO CALL: the user asks 'where am I', 'what's next', or 'am I Capstone-eligible'; before suggesting next-step coaching content. WHEN NOT TO CALL: as a heartbeat (state changes only when the user completes a stage); to read another user's progress. BEHAVIOR: read-only, idempotent. Auth: Bearer <token> (any plan, including basic). Returns user_email, course_slug, stages list with completion timestamps, certification block, and a next_stage hint.
    Connector
  • Scan a public GitHub MCP-server repository for security issues. Clones the repo (shallow, <60s, <200 MB), runs compuute-scan v0.6.2 in static analysis mode (no code execution from the target), and returns a structured report with severity counts, a 0-100 score, and the 10 most severe findings. WHEN TO USE: - Before connecting to an unknown MCP server discovered via Anthropic Registry, Smithery, mcp.so, or a Discord recommendation. - Before installing a third-party MCP-server package into a production pipeline. - As part of an agent's pre-commit / pre-deploy due-diligence step when adding new dependencies. - As one input to a multi-source trust evaluation (combine with publisher reputation, package install count, last-update recency). WHEN NOT TO USE: - For private repos. Use the on-prem CLI instead: `npx compuute-scan ./path-to-private-repo` - For deep exploitability assessment of a specific code path. This is pattern matching, not dataflow analysis. Book a manual L2-L4 audit at https://compuute.se/audit for that depth. - For non-GitHub hosts (GitLab, Bitbucket, self-hosted). v1 supports github.com only. - For repos > 200 MB or clone time > 60s. The endpoint returns a 413 or 504 in those cases — fall back to local CLI. EXPECTED RESPONSE TIME: - Median: ~1-2 seconds for small repos (<100 files). - p99: ~10 seconds for medium repos. - Hard timeout at clone=60s, scan=120s combined. EXPECTED COST: - Free tier in MVP. Future Pro tier may charge per-scan or per-month. DATA FRESHNESS: - Scanner version is reported in response.scanner.version. - L1 rule set freshness reflects compuute-scan releases — see github.com/Compuute/compuute-scan/CHANGELOG.md for the latest CVE and threat-intel response timeline. EXAMPLES: Example 1 — scan an MCP server you're evaluating: github_url = "https://github.com/modelcontextprotocol/servers" → score: 0, summary: {critical: 1, high: 94, medium: 22} → top_findings include SSRF, eval, etc. → recommendation: "AVOID — 1 critical and 94 high finding(s)..." Example 2 — scan a clean reference implementation: github_url = "https://github.com/microsoft/azure-devops-mcp" → score: 90+, summary: {critical: 0, high: 1} → recommendation: "REVIEW — 1 high finding(s)..." Example 3 — scan your own dev MCP-server before publishing: github_url = "https://github.com/yourorg/your-mcp" → audit your own surface before others install it OUTPUT FIELDS (stable schema): - repo_url (str): canonical URL of the scanned repo. - score (int): 0-100, higher safer. Coarse summary, not a precision claim. - summary (object): {critical, high, medium, low, info, files_scanned}. - recommendation (str): action guidance derived from severity counts. - findings_count (int): total raw findings (may include false positives). - top_findings (list): up to 10 most severe, each with {id, title, severity, file, line, owasp, cwe}. - l0_discovery (object): MCP transport, tool count, dependency pinning. - performance (object): clone_seconds, scan_seconds, repo_size_bytes. - scanner (object): {name, version, layers_covered}. - _disclaimer (str): MANDATORY triage disclaimer. Read it. Args: github_url: Public GitHub HTTPS URL (e.g. https://github.com/org/repo). Must be public and < 200 MB. v1 is github.com only. Returns: Structured scan result. On error, returns {"error": code, "message": ...} with HTTP-style code (invalid_url, clone_failed, scan_timeout, etc.).
    Connector
  • Authenticated — returns the caller's Blueprint learning-path state: current course slug, stage progress, certification status (Foundation, Practitioner, Capstone), Capstone track eligibility flags, and the next recommended stage. WHEN TO CALL: the user asks 'where am I', 'what's next', or 'am I Capstone-eligible'; before suggesting next-step coaching content. WHEN NOT TO CALL: as a heartbeat (state changes only when the user completes a stage); to read another user's progress. BEHAVIOR: read-only, idempotent. Auth: Bearer <token> (any plan, including basic). Returns user_email, course_slug, stages list with completion timestamps, certification block, and a next_stage hint.
    Connector
  • Free buyer-side search across Ontario's fresh strict-ready paid profiles, Agentic Market, and Coinbase CDP Bazaar. Rank public, credential-free endpoint candidates by task relevance plus bounded source-reported recent activity, with optional Base/USDC budget filtering. Paid Ontario publication adds no ranking score. This is discovery, not a safety certification; run readiness and can-pay before spending. When the query is provider-side publication intent, skip buyer marketplace search and return the free listing validator followed by the gated 0.50 USDC publication workflow.
    Connector
  • Explain how Tollbooth certification taxation works. Taxation is ad valorem and **per-Authority** — there is no single network-wide number, and the Oracle deliberately quotes none. The actual fee is the Authority's own accounting, set in its pricing model and reported at transaction time. This tool is a docent: it explains the model and points to the live source. For the exact figure, query the relevant Authority's ``check_price`` for ``certify_credits``.
    Connector

Matching MCP Servers

  • F
    license
    C
    quality
    D
    maintenance
    A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.
    3
    23
    1
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.
    MIT

Matching MCP Connectors

  • Search 5,000+ trading papers with verified backtests, strategies, datasets, and courses.

  • Your AI agent builds interactive block-based courses over MCP; take them at learnwithagents.app.

  • Explain the DPYC Social Contract economic model — qualitatively. Describes how value flows through the network: ad valorem certification fees, the cascade up the Certification Chain to the First Curator, and where the live numbers actually live. The Oracle quotes **no** rates, counts, or revenue figures — those belong to the Authorities' pricing models and the live registry, not to a docent. Free, unauthenticated.
    Connector
  • Search the Analytics Legends Academy — the written training modules on SAP Datasphere, Business Data Cloud, SAP Analytics Cloud, BW/4HANA and Databricks — by track, level and free text. `_meta.tranche_total_row_count` carries the live catalogue size on every call; it is the only count to quote. Returns the catalogue entry: id, slug, EN/FR title, track, level, duration in minutes, tags and the editor's summary. DO NOT CONFUSE IT WITH `list_sap_modules`, which serves a different population under the same word: that one is the 40-row PRODUCT taxonomy (codes such as SAC, DATASPHERE) used to normalise product wording. This one is the course catalogue. Without `query`, rows come back in the catalogue's own CURRICULUM order — the order a reader is meant to take them in — track by track. This catalogue is written training, NOT SAP certification tracks: this server publishes no certification data at any tier, so a certification question has no answer here rather than a partial one. CATALOGUE ONLY — the module BODY is subscriber content, served by `get_academy_module` on this same endpoint with a subscriber key (Consultant tier or above), which is the same door the €29.90 Consultant Pass opens on the site. On THIS endpoint the machine-access subscription is the MCP Pass (€39.90/month, analyticslegends.ai/pricing/), which opens the ENTIRE paid tranche from one key; the €29.90 Consultant Pass is its web-subscriber equivalent and opens the same tier floor here. `status` and `is_preview` are SERVED, never filtered on: they are the two flags the platform marks free access with, they do not coincide (measured 2026-08-16: 38 rows `status='available'`, 56 rows `is_preview`), and you decide which one your answer needs. PAGINATED: pass `_meta.next_cursor` back as `cursor` with the same filters until it is null. Read `_meta.available_tracks` and `_meta.available_levels` — both counted on the served population at call time — before assuming a facet value exists.
    Connector
  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
    Connector
  • List images for a brand. Filter by PowerSource (this scan only, via powersource_id), by on-pack product_name (the vision tagger's read), by type (logo, product, product_cutout, hero, lifestyle, ingredient, packaging, certification, before_after, infographic, screenshot, video, general), or by is_primary_product. Use this BEFORE generating any image-based output so you pick from the brand's real assets, not generic stock. Returns asset_id, signed url, type, detected_product_name, is_primary_product, sources. Free, read-only. Paginated via cursor.
    Connector
  • Get SaSame-observed MCP server recommendations for a capability you need. SaSame, operated by SASAME S.R.L., continuously observes and measures the Model Context Protocol ecosystem and publishes verifiable evidence and history; the MCP Factory is internal machinery and an optional product surface behind it; measurement only, not endorsement. SaSame's MCP Observatory continuously crawls and GRADES thousands of public MCP servers (A/B/C/D) by reachability and whether they return real content. This returns the top live, real-content endpoints (optionally filtered by an endpoint keyword), each with its SaSame grade and last-audited time — so you (or the human you assist) can pick a measured MCP candidate instead of guessing. Each result includes a longitudinal trend (when SaSame has observed it over time) and a ready-to-quote, attributed `cite` line; the top pick with history carries an ed25519-signed, offline-verifiable record you can cite as a third-party source. Free, read-only, no signup. If you operate one of these servers, claim it (claim_start). If you can't find a fit and need an MCP/agent BUILT, call engage_sasame. Pass a referral handle from `refer` as engage_sasame(ref=...) to attribute the introduction.
    Connector
  • Hosted-safe unsigned builder for create_escrow_v2. Use this from hosted SAP MCP, preview the result, then call local sap_payments_finalize_transaction with submit:true. The depositorWallet signs locally; keypair bytes never leave the user machine. Defaults to DisputeWindow settlementSecurity=2 and rejects SelfReport/0. SAP MCP context: Hosted-safe unsigned Escrow V2 builder. The output is not submitted and is not signed by hosted SAP MCP. Preview it, then call local sap_payments_finalize_transaction with submit:true and confirm:true. Never create temporary signing scripts or read keypair JSON. SAP MCP execution guidance: Intent: hosted unsigned transaction builder. Pricing: paid builder; estimate first, then pay/build and finalize unsigned transactions locally when returned. Routing: hosted-safe builder. If a transaction is returned, preview/sign/submit with sap_payments_finalize_transaction; never create temporary signing scripts. Signer boundary: user-controlled local profile or external signer; OOBE hosted MCP remains non-custodial.
    Connector
  • Explains how to connect an account to this MCP server — read this instead of guessing at a login/registration tool, because there isn't one. ClusterHack's own credential endpoints (register, login, JWT issuance, password reset) are the website's login form, not MCP tools: an MCP client authenticates by OAuth 2.1 (the same flow a human approves in a browser tab) and must never see or handle a ClusterHack password directly. This tool works with no account at all, and just explains the steps and links.
    Connector
  • Produce a deterministic remediation REQUEST bundle (rubric + fix schema + per-finding metadata + fingerprints) for YOU (the host agent) to fix. This tool calls no model and needs no key. For each finding, propose the corrected FULL file content, then VERIFY with verify_fix and keep only fixes that clear the finding. Never touch files with secrets; never auto-merge. Pass 'findings' from scan_path --format json.
    Connector
  • Runs JavaScript code to interact with the Mux API. You are a skilled TypeScript programmer writing code to interface with the service. Define an async function named "run" that takes a single parameter of an initialized SDK client and it will be run. For example: ``` async function run(client) { const asset = await client.video.assets.create({ inputs: [{ url: 'https://storage.googleapis.com/muxdemofiles/mux-video-intro.mp4' }], playback_policies: ['public'] }); console.log(asset.id); } ``` You will be returned anything that your function returns, plus the results of any console.log statements. Do not add try-catch blocks for single API calls. The tool will handle errors for you. Do not add comments unless necessary for generating better code. Code will run in a container, and cannot interact with the network outside of the given SDK client. Variables will not persist between calls, so make sure to return or log any data you might need later. Remember that you are writing TypeScript code, so you need to be careful with your types. Always type dynamic key-value stores explicitly as Record<string, YourValueType> instead of {}.
    Connector
  • Terse, drill-down discovery index of this ecosystem (Seneschal, FlashBank, winbit32, secresea, ZecBus, Zecmon, Ziving, Bit ID, McPai) plus a LIVE mirror of the official MCP registry (registry.modelcontextprotocol.io) — the same directory served over HTTPS at https://seneschal.space/.well-known/agent.gopher, callable here so you never leave the MCP session. Start with section="root" to see the top-level menu, then call again with section="seneschal"/"flashbank"/"winbit32"/"secresea"/"zecbus"/"zecmon"/"ziving"/"bitid"/"mcpai" to drill into a project. Each project exposes About / Agents / Actions — drill them with section="<site>/about", "<site>/agents" or "<site>/actions" (e.g. "winbit32/actions"). Seneschal additionally drills into its own services with section="seneschal/<service>" where <service> is one of private-watch, checkout, oracle, shovels, builder, data, paymaster, board, ironwood, mcp — every website + MCP capability, grouped and priced. section="registry" browses connectable third-party MCP servers (use `cursor` to page); section="about"/"agents" is the directory’s own prose. format="gopher" (default) is the compact RFC-1436 menu; format="json" returns a structured {title, items[]}. A discovery layer, not a replacement for MCP — use it to FIND tools, then connect. Free, no payment.
    Connector
  • Get the wiki tag hierarchy with page counts per category. Useful for understanding what content exists, and for finding a valid tagPath before writing.
    Connector
  • Check any public URL RIGHT NOW: is it up, HTTP status, response time in ms. With kind:"mcp" it instead performs a real JSON-RPC initialize handshake against a streamable-HTTP MCP server endpoint and reports the server’s self-declared name/version/protocol — useful to tell "the MCP server is down" from "my client is misconfigured". Works without an API key (rate limit 30/hour per IP). For continuous monitoring with alerts, use create_monitor.
    Connector
  • Submit answers to the agent-track item set from get_bench_items. Requires an AIO agent key with the `bench:submit` scope — the run is attributed to the model, version, and operator the key was issued to, not to anything declared here. A layer must be answered in full (105 items) or omitted entirely. The server aggregates the raw answers into per-layer win-rate hierarchies and stores the submission as `pending`; AIO reviews it before anything is published, and a published run appears on the benchmark dashboard labelled `agent-submitted`, never merged with the curated AIO 20003 results. Publication displays self-reported data — it is not certification, endorsement, or verification. Ask the user before calling this.
    Connector
  • Choosing between several MCP servers that do similar things? This tool decides for you. PAID $0.10 via x402 (USDC micropayment over HTTP 402 — no account or API key needed; on your first call without payment you receive the exact payment requirements, then retry with the X-PAYMENT header). Compares 2-5 MCP servers head-to-head with identical objective checks (handshake, tools/list, documentation coverage, latency, and a safe functional probe — paid tools are never called) and returns: a ranked list, the recommended winner, a plain-language explanation of why it won, and each server's full report — cheaper than separate evaluate_mcp calls on 3+ servers. Objective checks only — no human and no LLM opinion; it does not judge the real-world usefulness or safety of the content. Set 'urls' (required) to an array of 2-5 MCP endpoints (Streamable HTTP), e.g. ["https://a/mcp","https://b/mcp"].
    Connector