Datasieve vs ProjectPulse MCP
A side-by-side look at the Datasieve and ProjectPulse MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Datasieve for monitoring work as a local process; choose ProjectPulse MCP for monitoring as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Datasieve when
- You need dedicated capabilities in the Monitoring domain.
- You prefer a local stdio subprocess transport.
- You want tools like
create_watch, watch_status, drain_events.
Choose ProjectPulse MCP when
- You need dedicated capabilities in the Monitoring domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
GITHUB_TOKEN. - You want tools like
check_ci_status, get_repo_health, analyze_dependencies.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Monitoring | Monitoring |
| Quality signal | 57/100 · Good | 64/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Free |
| Required env vars | None listed | GITHUB_TOKEN |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 1 |
| Directory activity | 1 views 0 installs 0 upvotes | 4 views 0 installs 0 upvotes |
| Tools | 19 | 8 |
| Full listing | View Datasieve | View ProjectPulse MCP |
Tools & capabilities
Datasieve tools 19
create_watchBuy a standing watch from DataSieve (https://api.datasieve.xyz). standard = $0.10/7d, 1 condition, 50 triggers; composite = $0.25/7d, up to 5 any-match conditions (e.g. 5 heartbeat dead-man switches), 200 triggers; standard30 = $0.35/30d and composite30 = $0.85/30d — one payment covers the month, for agents that will not be awake to renew weekly. Payment is a gasless USDC transfer signed locally. Events go to your webhookUrl (HMAC-signed) if set, and always to a server-side mailbox drained with drain_events; every event carries a signed Ed25519 observation receipt you can replay to third parties. Failed calls are never billed. The watch id + secret are remembered locally so later calls need only the id.watch_statusState, heartbeat lastCheckedAt, triggersUsed/cap, expiry, delivery stats, and for dead-man switches: up/down, lastPingAt, nextDeadline, pingUrl. Secret is looked up from local state if omitted.drain_eventsCollect everything the watch caught — works with zero infrastructure (the mailbox pattern). Pass `since` = last seen event id for incremental drains.renew_watchExtends the watch one more period (7 days, or 30 on the *30 tiers) at its tier price and resets the trigger budget. Renewing a paused watch also reactivates it.delete_watchpause_watchStop a watch firing (chain, web, heartbeat, schedule) without deleting it. The expiry clock keeps running. Use before a planned agent shutdown so your dead-man switch does not cry wolf.resume_watchBacklog-free resume: heartbeat deadlines restart from now and schedules jump to their next FUTURE slot — nothing that elapsed during the pause replays.cron_nextNext N run times for a cron expression in any IANA timezone, plus seconds-until-next. If the goal is for something to HAPPEN at those times, create_watch with a schedule condition instead — DataSieve fires the cron as signed webhooks for the life of the watch.x402_pingThe cheapest possible real x402 purchase: proves this wallet + client can pay a production seller before you point it at anything expensive. Returns payer + network; failed calls are never billed.verify_receiptEvery DataSieve event carries receipt {alg, keyId, statement, sig} — an Ed25519 attestation that DataSieve observed the event. This checks it against the service key, so an agent can validate evidence handed to it by ANOTHER agent without trusting that agent.ping_heartbeatKeep a dead-man switch alive. Pass the pingUrl from create_watch (or a watchId whose ping URLs are in local state). Call this at least once per intervalSeconds.service_healthScanner cursor lag vs chain head — verify the watcher is alive before you buy.- +7 more on the listing page
ProjectPulse MCP tools 8
check_ci_statusFetches recent CI/CD workflow runs (GitHub Actions) for a GitHub repository. - Side effects: None. This is a strictly read-only operation. - Data sources: GitHub REST API (actions/runs). - Auth requirements: No authentication required for public repositories. Uses configured token if available. - Rate limits: Subject to standard GitHub API limits. - Return shape: Returns a JSON array of workflow runs including name, status, conclusion, head_branch, created_at, updated_at, and html_url. - Usage guidelines: Use this tool ONLY to check raw GitHub Actions workflow history and CI build statuses. DO NOT use this tool for other analyses: - For a computed A-F health score grading, use 'get_health_score' instead. - For retrieving basic repository stats (stars, forks), use 'get_repo_health' instead. - For calculated DORA metrics, use 'get_dora_metrics' instead.get_repo_healthFetches basic repository metadata and statistics from the public GitHub API. - Side effects: None. This is a strictly read-only operation. - Data sources: Public GitHub REST API (GET /repos/{owner}/{repo}). - Auth requirements: No authentication required for public repositories. Uses configured GitHub token if available. - Rate limits: Subject to standard GitHub API limits (60 requests/hour unauthenticated, 5000 requests/hour authenticated). - Return shape: Returns a JSON object containing specific metadata: full_name (string), description (string), stargazers_count (number), open_issues_count (number), language (string), license (string, SPDX ID), pushed_at (ISO 8601 string), default_branch (string), archived (boolean), and forks_count (number). - Usage guidelines: Use this tool ONLY to retrieve basic raw metadata (like stars, forks, language, and issue counts). DO NOT use this tool for other specific analyses: - For a computed A-F health score grading, use 'get_health_score' instead. - For checking CI/CD workflow run statuses, use 'check_ci_status' instead. - For package vulnerabilities and dependency graph, use 'analyze_dependencies' instead. - For code security and static analysis, use 'analyze_code_scanning' instead.analyze_dependenciesFetches Dependabot alerts for a GitHub repository to analyze vulnerable package dependencies. - Side effects: None. This is a strictly read-only operation. - Data sources: GitHub REST API (dependabot/alerts). - Auth requirements: Requires GITHUB_TOKEN with appropriate permissions (dependabot alerts are often restricted). - Rate limits: Subject to standard GitHub API limits. - Return shape: Returns a JSON array of vulnerable package dependencies including summary, severity, package_name, state, and html_url. - Usage guidelines: Use this tool ONLY to find vulnerable package dependencies (npm, pip, etc.). DO NOT use this tool for other checks: - For static code security vulnerabilities (CodeQL), use 'analyze_code_scanning' instead. - For a computed A-F health score grading, use 'get_health_score' instead.analyze_code_scanningFetches or triggers open Code Scanning (CodeQL) alerts for a GitHub repository. - Side effects: Read-only by default. If trigger_scan=true, writes to GitHub Actions by creating a workflow_dispatch event. - Data sources: GitHub REST API (code-scanning/alerts and actions). - Auth requirements: Requires GITHUB_TOKEN with appropriate permissions (security-events). - Rate limits: Subject to standard GitHub API limits. - Return shape: Returns a JSON array of alert objects including rule_id, severity, rule_description, state, location paths, and html_url. - Usage guidelines: Use this tool ONLY for deep static code vulnerability scanning (CodeQL). DO NOT use this tool for other checks: - For package/dependency vulnerabilities, use 'analyze_dependencies' instead. - For a computed A-F health score grading, use 'get_health_score' instead. - For checking standard CI/CD workflow statuses, use 'check_ci_status' instead.get_health_scoreCalculates a 0-100 health score and A-F grade for a GitHub repository. - Side effects: Writes a trend snapshot to local disk for history tracking. Read-only against GitHub API. - Data sources: GitHub REST API (repos, actions, dependabot) and OpenSSF Scorecard API. - Auth requirements: No authentication required for public repositories. Uses configured token if available. - Rate limits: Subject to standard GitHub API limits (heavy usage across multiple endpoints). - Return shape: Returns a JSON object with a grade (A-F), total score, detailed category breakdown (CI, freshness, security, community, maintenance), improvement suggestions, and historical trend data. - Usage guidelines: Use this tool ONLY for deep analytical grading and overall repository health assessment. DO NOT use this tool for quick metadata checks: - For basic raw metadata (stars, language, etc.), use 'get_repo_health' instead. - For raw CI workflow statuses, use 'check_ci_status' instead. - For deep code vulnerability scanning, use 'analyze_code_scanning' instead. - For DORA metrics, use 'get_dora_metrics' instead.get_dora_metricsCalculates DORA proxy metrics (deployment frequency, lead time, change failure rate, MTTR) for a GitHub repository. - Side effects: None. This is a strictly read-only operation. - Data sources: GitHub REST API (releases, actions/runs, pulls). - Auth requirements: No special authentication required for public repositories. Private repositories require GITHUB_TOKEN. - Rate limits: Subject to standard GitHub API limits. Heavy API usage due to multiple list endpoints being queried. - Return shape: Returns a JSON object with calculated DORA metrics over the specified period. - Usage guidelines: Use this tool ONLY to evaluate DORA metrics and team delivery performance. DO NOT use this tool for other checks: - For raw workflow statuses, use 'check_ci_status' instead. - For a computed A-F health score grading, use 'get_health_score' instead. - For general repository metadata, use 'get_repo_health' instead.compare_reposCompares health scores of multiple GitHub repositories (2-5 repos) and ranks them. - Side effects: None. This is a strictly read-only operation. - Data sources: GitHub REST API and OpenSSF Scorecard API (via get_health_score logic). - Auth requirements: No authentication required for public repositories. Uses configured token if available. - Rate limits: Subject to standard GitHub API limits. Multiplies API calls by the number of repositories compared. - Return shape: Returns a JSON object containing a ranked list of repositories (owner, repo, rank) with their detailed health breakdown (score, CI, freshness, security, community, maintenance). - Usage guidelines: Use this tool ONLY when you need to compare or rank multiple repositories against each other based on their health scores. DO NOT use this tool for analyzing a single repository: - For getting the health score of a single repository, use 'get_health_score' instead. - For comparing raw metadata instead of health scores, query 'get_repo_health' individually.check_best_practicesChecks whether a GitHub repository follows open-source community best practices. - Evaluates 12 checks: README, LICENSE, SECURITY.md, CONTRIBUTING.md, CODE_OF_CONDUCT, issue/PR templates, branch protection, Dependabot, CI/CD, description, and topics. - Returns a weighted 0-100 score with A-F grade, per-check pass/fail/unknown status, and actionable suggestions for missing items. - Side effects: None. Read-only operation. - Rate limits: ~6 GitHub API calls per invocation. - Branch protection check requires admin access — returns "unknown" (not penalized) if token lacks permission. - Use this tool to audit repo quality and discoverability. For a computed health grade based on CI/security/activity, use 'get_health_score' instead.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Datasieve
{
"mcpServers": {
"datasieve": {
"command": "npx",
"args": [
"-y",
"datasieve-mcp"
]
}
}
}
ProjectPulse MCP
{
"mcpServers": {
"projectpulse-mcp": {
"command": "npx",
"args": [
"-y",
"projectpulse-mcp"
],
"env": {
"GITHUB_TOKEN": "YOUR_GITHUB_TOKEN_HERE"
}
}
}
}
Frequently asked questions
Datasieve is categorized under Monitoring and uses a local stdio subprocess. ProjectPulse MCP belongs to Monitoring and uses a local stdio subprocess. Pick Datasieve for monitoring work and ProjectPulse MCP for monitoring.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Datasieve has no declared pricing — check the project's own site. ProjectPulse MCP is listed as free. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add datasieve and projectpulse-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Datasieve has a quality signal of 57/100 (Good) with 1 views, 0 installs and 0 GitHub stars. ProjectPulse MCP has 64/100 (Good) with 4 views, 0 installs and 1 GitHub stars.