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755,807 tools. Updated 2026-11-07 13:08

"A service for reviewing and improving Overleaf resumes" matching MCP tools:

  • Change an existing automation by id. action=disable stops it firing (use this to turn off a misbehaving rule); action=enable resumes it; action=delete removes it. To read one, use relm_get_automation. To change a rule's trigger/conditions/actions, delete and recreate.
    Connector
    Destructive
    No auth
  • Returns the organization's development standards: coding conventions, project structure, and framework-specific rules. Read-only. Call it before writing or reviewing code, so the result follows this organization's rules rather than general defaults. Call it first without a section to get an index of available sections, each with a note on what it covers, then call again with one section id copied from that index; inventing a section id returns a not-found error naming that step. Request only the sections a task needs - the full content of one section can be long. The framework argument is deprecated: use section with the "framework:" prefix instead. It returns prose rules, not data - use get_style_tokens for visual values and get_component for component APIs.
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  • Returns per-component breaking changes and a migration guide between an installed version of the project's active component package and the latest published version. Read-only: it reports an upgrade, it never performs one. Use it when planning or reviewing a component-library upgrade, or before bumping the package version in a manifest. current_version is the exact semver currently installed, e.g. "1.0.0" - not a range, so no leading "v", "^", or "~"; read it from list_packages when unsure. Passing the latest version returns an empty change set. It is not a per-component changelog and not a current spec - use get_component for one component today, and list_packages for what is installed. Requires update tracking, a Team plan feature; on lower plans it returns an upgrade-required error instead of data.
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  • The merge gate for ANY AI-written output — code, documentation, reports, emails, configs: returns a binary approve/reject verdict with veto power — e.g. it rejects code calling the nonexistent stripe.Inventory API, an N+1 loop with the latency arithmetic to prove it, or a doc claiming success with no evidence. Deterministic reality gates (mock/placeholder veto, gaming and bypass detection, invented-API checks) run first and cannot be overridden; a frontier-model review (ISO/IEC 25010) then scores quality, accuracy, reliability and tech debt. In a benchmark, a frontier model reviewing alone caught reward-gaming and hallucinated APIs 0/6 times in a natural review workflow; these gates catch them deterministically on every call. Read-only: nothing is executed. Call it on every AI-generated deliverable before accepting it; use validate_plan for plans, analyze_code for an advisory report without a verdict.
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  • List the layers of a Baltimore ArcGIS service (for discovery). Pass a known short name (crime, service_requests, permits) or a full ArcGIS service path (e.g. "311_Customer_Service_Requests_current/FeatureServer"). Omit `service` to list the known Baltimore services. Returns layer id + name to use with baltimore_query.
    ConnectorNo auth
  • Leave a comment on a post the user is reviewing, wrote, or can see as an admin. It decides and blocks nothing: for a verdict use approve_post or send_back_post. Use for feedback, a question, or a note. The text is stored verbatim, so pass the user's own words. The author and the other reviewers are notified. Ids come from list_posts_awaiting_my_review or list_drafts.
    ConnectorOAuth

Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI agents to recall evidence-backed public reviews of tools, products, APIs, and services before recommending them, and to submit new reviews after use via a human-approved proposal flow. Also supports searching items, fetching items and their reviews, and offloading proposals through a shared, account-free review database.
    MIT

Matching MCP Connectors

  • Public AI-written review DB. recall before recommending; propose after use.

  • Create and edit saved resumes, make tailored or translated copies, and export PDF or Word.

  • Full Rams design review of UI code (React, Vue, Svelte, HTML, CSS, SwiftUI). Returns a 0-100 score (criticals cap it: one caps at 59, two at 49, three or more at 39), issues with severity, category, file:line, and concrete fixes as patches. Call it once at the end: before a commit, or when the user wants a score or a final check. Pass each file with its real path, or for pasted code a path that fits it (pasted/Card.tsx). Each call uses one review credit. Reviewing a few files needs no permission. Ask the user before a whole-codebase audit (dozens of files), since it spends their allowance. For quick feedback while you work, use quick_review.
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  • Full Rams design review of UI code (React, Vue, Svelte, HTML, CSS, SwiftUI). Returns a 0-100 score (criticals cap it: one caps at 59, two at 49, three or more at 39), issues with severity, category, file:line, and concrete fixes as patches. Call it once at the end: before a commit, or when the user wants a score or a final check. Pass each file with its real path, or for pasted code a path that fits it (pasted/Card.tsx). Each call uses one review credit. Reviewing a few files needs no permission. Ask the user before a whole-codebase audit (dozens of files), since it spends their allowance. For quick feedback while you work, use quick_review.
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  • BATCH INSPECTION: run up to 32 AWS inspect probes in one call. ⚠️ **PREREQUISITE**: Same as awsinspect — deploy attempt required. Check convostatus for hasDeployAttempt=true before calling. Use this when you need to check more than ~3 resources. The backend fetches Oracle credentials ONCE per batch and fans out probes against a single AWS config — for a 12-resource health check this is ~5–8× faster and 12× fewer Oracle round-trips than calling awsinspect 12 times. BUDGETS: - Up to 32 sub-probes per call (subs array length). - 30s per-sub timeout; 60s total batch wall-clock. - Concurrency cap 8 — sub-probes run in parallel but never saturate AWS. - 512 KB response cap: subs past the cap keep their envelope (index/service/action/ok) but have result replaced with truncated=true. PARTIAL FAILURE IS EXPECTED. The response is an ordered results array; each entry has {index, service, action, ok, result, error}. Inspect each result — do NOT abort on the first error. A credential fetch failure leaves cred-less probes (list-actions, list-metrics) succeeding anyway. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: account, acm, alb, apigateway, apprunner, backup, bedrock, cloudfront, cloudwatchlogs, cognito, cost-explorer, dynamodb, ebs, ec2, ecs, eks, elasticache, kms, lambda, msk, opensearch, rds, route53, s3, sagemaker, secretsmanager, sqs, vpc, waf For a specific service's actions, use awsinspect (singular) with action="list-actions" — batch is not the place for discovery. Batch responses are always summarized (no detail/raw per-sub); use singular awsinspect when you need full metadata or raw API output for one resource. EXAMPLES: - awsinspect_batch(session_id=..., subs=[ {"service":"ec2","action":"describe-instances"}, {"service":"rds","action":"describe-db-instances"}, {"service":"vpc","action":"describe-vpcs"}, {"service":"s3","action":"list-buckets"}]) - awsinspect_batch(session_id=..., subs=[ {"service":"ec2","action":"get-metrics","filters":"{\"hours\":6}"}, {"service":"rds","action":"get-metrics","filters":"{\"hours\":6}"}])
    ConnectorNo auth
  • BATCH INSPECTION: run up to 32 GCP inspect probes in one call. ⚠️ **PREREQUISITE**: Same as gcpinspect — deploy attempt required. Check convostatus for hasDeployAttempt=true before calling. Use this when you need to check more than ~3 resources. The backend fetches Oracle credentials ONCE per batch and fans out probes against a single GCP credentials blob — a 12-resource health check is ~5–8× faster and 12× fewer Oracle round-trips than calling gcpinspect 12 times. BUDGETS: - Up to 32 sub-probes per call (subs array length). - 30s per-sub timeout; 60s total batch wall-clock. - Concurrency cap 8. - 512 KB response cap: subs past the cap keep their envelope (index/service/action/ok) but have result replaced with truncated=true. PARTIAL FAILURE IS EXPECTED. The response is an ordered results array; each entry has {index, service, action, ok, result, error}. Inspect each result — do NOT abort on the first error. A credential fetch failure leaves cred-less probes (list-actions, list-metrics) succeeding anyway. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: apigateway, bastion, billing, certificatemanager, cloudarmor, cloudbuild, cloudcdn, clouddeploy, clouddns, cloudfunctions, cloudkms, cloudlogging, cloudmonitoring, cloudrun, cloudsql, compute, firestore, gcs, gke, iam, identityplatform, loadbalancer, memorystore, pubsub, secretmanager, vertexai, vpc For a specific service's actions, use gcpinspect (singular) with action="list-actions" — batch is not the place for discovery. Batch responses are always summarized (no detail/raw per-sub); use singular gcpinspect when you need full metadata or raw API output for one resource. EXAMPLES: - gcpinspect_batch(session_id=..., subs=[ {"service":"compute","action":"list-instances"}, {"service":"gke","action":"list-clusters"}, {"service":"cloudsql","action":"list-instances"}]) - gcpinspect_batch(session_id=..., subs=[ {"service":"compute","action":"get-metrics","filters":"{\"hours\":6}"}, {"service":"cloudrun","action":"get-metrics","filters":"{\"hours\":6}"}])
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  • Check available appointment slots for a specific service at a local business on a given date. This calls the business's configured availability provider live and fails closed when the provider fails. Returns time windows when the business is free and the service bookingStartPolicy permits the start. For services with maxParticipants > 1, provider-returned starts remain available until capacity is full. ONLY call this if the business has 'booking' in its enabledFeatures array. If the business doesn't support booking, share their contact info from get_business_info instead.
    ConnectorNo auth
  • BATCH INSPECTION: run up to 32 AWS inspect probes in one call. ⚠️ **PREREQUISITE**: Same as awsinspect — deploy attempt required. Check convostatus for hasDeployAttempt=true before calling. Use this when you need to check more than ~3 resources. The backend fetches Oracle credentials ONCE per batch and fans out probes against a single AWS config — for a 12-resource health check this is ~5–8× faster and 12× fewer Oracle round-trips than calling awsinspect 12 times. BUDGETS: - Up to 32 sub-probes per call (subs array length). - 30s per-sub timeout; 60s total batch wall-clock. - Concurrency cap 8 — sub-probes run in parallel but never saturate AWS. - 512 KB response cap: subs past the cap keep their envelope (index/service/action/ok) but have result replaced with truncated=true. PARTIAL FAILURE IS EXPECTED. The response is an ordered results array; each entry has {index, service, action, ok, result, error}. Inspect each result — do NOT abort on the first error. A credential fetch failure leaves cred-less probes (list-actions, list-metrics) succeeding anyway. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: account, acm, alb, apigateway, apprunner, backup, bedrock, cloudfront, cloudwatchlogs, cognito, cost-explorer, dynamodb, ebs, ec2, ecs, eks, elasticache, kms, lambda, msk, opensearch, rds, route53, s3, sagemaker, secretsmanager, sqs, vpc, waf For a specific service's actions, use awsinspect (singular) with action="list-actions" — batch is not the place for discovery. Batch responses are always summarized (no detail/raw per-sub); use singular awsinspect when you need full metadata or raw API output for one resource. EXAMPLES: - awsinspect_batch(session_id=..., subs=[ {"service":"ec2","action":"describe-instances"}, {"service":"rds","action":"describe-db-instances"}, {"service":"vpc","action":"describe-vpcs"}, {"service":"s3","action":"list-buckets"}]) - awsinspect_batch(session_id=..., subs=[ {"service":"ec2","action":"get-metrics","filters":"{\"hours\":6}"}, {"service":"rds","action":"get-metrics","filters":"{\"hours\":6}"}])
    ConnectorNo auth
  • BATCH INSPECTION: run up to 32 GCP inspect probes in one call. ⚠️ **PREREQUISITE**: Same as gcpinspect — deploy attempt required. Check convostatus for hasDeployAttempt=true before calling. Use this when you need to check more than ~3 resources. The backend fetches Oracle credentials ONCE per batch and fans out probes against a single GCP credentials blob — a 12-resource health check is ~5–8× faster and 12× fewer Oracle round-trips than calling gcpinspect 12 times. BUDGETS: - Up to 32 sub-probes per call (subs array length). - 30s per-sub timeout; 60s total batch wall-clock. - Concurrency cap 8. - 512 KB response cap: subs past the cap keep their envelope (index/service/action/ok) but have result replaced with truncated=true. PARTIAL FAILURE IS EXPECTED. The response is an ordered results array; each entry has {index, service, action, ok, result, error}. Inspect each result — do NOT abort on the first error. A credential fetch failure leaves cred-less probes (list-actions, list-metrics) succeeding anyway. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: apigateway, bastion, billing, certificatemanager, cloudarmor, cloudbuild, cloudcdn, clouddeploy, clouddns, cloudfunctions, cloudkms, cloudlogging, cloudmonitoring, cloudrun, cloudsql, compute, firestore, gcs, gke, iam, identityplatform, loadbalancer, memorystore, pubsub, secretmanager, vertexai, vpc For a specific service's actions, use gcpinspect (singular) with action="list-actions" — batch is not the place for discovery. Batch responses are always summarized (no detail/raw per-sub); use singular gcpinspect when you need full metadata or raw API output for one resource. EXAMPLES: - gcpinspect_batch(session_id=..., subs=[ {"service":"compute","action":"list-instances"}, {"service":"gke","action":"list-clusters"}, {"service":"cloudsql","action":"list-instances"}]) - gcpinspect_batch(session_id=..., subs=[ {"service":"compute","action":"get-metrics","filters":"{\"hours\":6}"}, {"service":"cloudrun","action":"get-metrics","filters":"{\"hours\":6}"}])
    ConnectorNo auth
  • Set carrier-specific advanced shipping options (Service flags, COD) and CustomsOptions. For the common sparse options — InsuranceType and Delivery.Signature / Delivery.Residential — prefer teapplix_update_order with Options (ShipOptions) instead, which handles them in a single call alongside other fields without requiring Packages. Use this tool only when you need Service, COD, or CustomsOptions fields not covered by updateOrder.Options. When Packages is provided here, it replaces all existing package definitions. [DEMO]
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  • Create a database user for a Cloud SQL instance. * This tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes. * When you use the `create_user` tool, specify the type of user: `CLOUD_IAM_USER`, `CLOUD_IAM_SERVICE_ACCOUNT`, or `BUILT_IN`. * By default the newly created user is assigned the `cloudsqlsuperuser` role, unless you specify other database roles explicitly in the request. * You can use a newly created user with the `execute_sql` tool if the user is a currently logged in IAM user. The `execute_sql` tool executes the SQL statements using the privileges of the database user logged in using IAM database authentication. The `create_user` tool has the following limitations: * To create a built-in user with password, use the `password_secret_version` field to provide password using the Google Cloud Secret Manager. The value of `password_secret_version` should be the resource name of the secret version, like `projects/12345/locations/us-central1/secrets/my-password-secret/versions/1` or `projects/12345/locations/us-central1/secrets/my-password-secret/versions/latest`. The caller needs to have `secretmanager.secretVersions.access` permission on the secret version. * The `create_user` tool doesn't support creating a user for SQL Server. To create an IAM user in PostgreSQL: * The database username must be the IAM user's email address and all lowercase. For example, to create user for PostgreSQL IAM user `example-user@example.com`, you can use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance":"test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user@example.com`. To create an IAM service account in PostgreSQL: * The database username must be created without the `.gserviceaccount.com` suffix even though the full email address for the account is`service-account-name@project-id.iam.gserviceaccount.com`. For example, to create an IAM service account for PostgreSQL you can use the following request format: ``` { "name": "test@test-project.iam", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `test@test-project.iam`. To create an IAM user or IAM service account in MySQL: * When Cloud SQL for MySQL stores a username, it truncates the @ and the domain name from the user or service account's email address. For example, `example-user@example.com` becomes `example-user`. * For this reason, you can't add two IAM users or service accounts with the same username but different domain names to the same Cloud SQL instance. * For example, to create user for the MySQL IAM user `example-user@example.com`, use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user`. * For example, to create the MySQL IAM service account `service-account-name@project-id.iam.gserviceaccount.com`, use the following request: ``` { "name": "service-account-name@project-id.iam.gserviceaccount.com", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `service-account-name`.
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  • Return the durable work queue for Research Bounties created by this exact Bearer agent key. Call after funding, whenever the agent starts or resumes, when the controller receives a RigorLoop alert, or at an operator-approved interval while work remains active. Each item includes funding, applications, assignment, result state, and the next recommended tool call. Do not assume email access; stop routine checks after completion or cancellation.
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  • Release an engaged Emergency Brake, re-enabling exactly the campaigns it paused (and only those still paused — a campaign the user changed since is left alone). mode='raise' re-arms the brake against the budget's current amount for the rest of the month; mode='resume' means the user knowingly overrules the budget, so that level stays disarmed until next month. Re-enables live campaigns and therefore resumes real ad spend — confirm intent first.
    Connector
    Destructive
    API key
  • Pair this MCP session with a browser tab on the hosted Valem sandbox so both drive the same live model session. Mints a pairing on first call (or resumes an existing not-yet-approved one) and waits up to a minute for the developer to approve it. Returns {status:"paired"|"already_paired", namespaceId} once done, or {status:"pending", verificationUri, verificationUriComplete, userCode, expiresInSec} if the developer hasn't approved yet — show them verificationUriComplete when present (it already carries the confirmation code, so they only click Approve) and mention that the code on that screen should read userCode; fall back to verificationUri, which requires them to TYPE userCode. Then call this tool again (it resumes the SAME pairing, it does not mint a new one). Every other model tool (create_model, mutate, evolve_spec, get_state, explain, ...) fails with a clear error until pairing succeeds.
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  • Builds an unsigned transaction blueprint for placing a bid on a Gavel auction, including the prerequisite ERC-20 approval when the current allowance is short. You supply the auction and the repayment amount you are willing to accept; this tool validates them against live auction state and encodes the call. It does not choose an auction, a rate or a size for you — use find_auctions_matching_criteria to filter by your own criteria first. Bidding on Gavel is a reverse auction: a LOWER repayment is a more competitive bid and a lower yield to you as lender. Each bid must undercut the current best by at least the auction's bid step. Returns an unsigned transaction blueprint for the requested intent. The user is responsible for reviewing, signing, and broadcasting via their own wallet. Aletheia does not hold keys or dispatch transactions.
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  • Answers: after a change was made, did this store's revenue signals actually recover? Compares the window before a stated change against the window since: paid vs pending vs failed order mix, webhook failure counts, and gateway availability. Returns `resolved`, `improving`, `still_failing`, or `unknown` — and `unknown` when too little new data has arrived to tell, which is free. A quiet ten minutes is not a recovery. Free while in beta.
    ConnectorNo auth
  • Answers: after a change was made, did this store's revenue signals actually recover? Compares the window before a stated change against the window since: paid vs pending vs failed order mix, webhook failure counts, and gateway availability. Returns `resolved`, `improving`, `still_failing`, or `unknown` — and `unknown` when too little new data has arrived to tell, which is free. A quiet ten minutes is not a recovery. Free while in beta.
    ConnectorNo auth