Supported Capabilities
RChilli MCP Integration provides access to multiple RChilli capabilities through supported AI assistants.
Customers can use these capabilities to process resumes and job descriptions, standardize recruitment data, compare candidates with jobs, anonymize resumes, and search indexed documents.
The exact capabilities available to a customer depend on the subscribed RChilli services and the tools enabled in the MCP configuration.
Resume Parsing
Resume Parsing converts an unstructured resume into structured recruitment data.
Depending on the available information in the resume, the output may include:
- Candidate name
- Contact information
- Skills
- Employment history
- Job profiles
- Employers
- Work periods
- Total experience
- Education
- Qualifications
- Certifications
- Languages
- Achievements
- Locations
Users can ask the AI assistant to parse a resume and present only the information relevant to their task.
Example:
Parse this resume and show the candidate’s current job profile, total experience, key skills, and highest qualification.
The resume may be provided as supported text or through a document URL, depending on the AI client and configured RChilli tool.
Job Description Parsing
Job Description Parsing converts an unstructured job posting into structured information.
The returned data may include:
- Job profile
- Required skills
- Preferred skills
- Experience requirements
- Qualifications
- Salary information
- Job location
- Roles and responsibilities
- Job taxonomy information
Example:
Parse this job description and list the required skills, preferred skills, minimum experience, and qualifications.
The structured output can be used for candidate matching, search, validation, or recruitment analytics.
Resume and Job Description Matching
Customers can compare a candidate resume with a job description and receive an explainable matching result.
The result may help users understand:
- Overall matching score
- Job profile alignment
- Matching skills
- Missing skills
- Experience alignment
- Qualification alignment
- Location alignment
- Other configured matching parameters
Example:
Compare this resume with the job description and explain the matching score.
A one-to-one comparison can be performed without first adding the resume and job description to an index.
Search and Match
Customers with indexed resume or job description data can search documents and retrieve relevant results.
Supported activities may include:
- Searching indexed resumes or job descriptions
- Finding candidates based on skills or experience
- Finding suitable jobs for a candidate
- Matching one document against an indexed collection
- Ranking results based on relevance
Examples:
Find candidates with Java, Spring Boot, microservices, and AWS experience.
Rank the indexed candidates against this job description.
Find jobs that are relevant to this candidate’s profile.
Search and corpus-level matching require the relevant documents to be available in the applicable RChilli index.
Skill Taxonomy
Skill Taxonomy helps customers validate and standardize skill information.
Depending on the available taxonomy data, a skill lookup may return:
- Standardized skill name
- Description
- Aliases
- Related skills
- Skill classification
- Ontology information
- Industry-standard mappings
Example:
Look up the standardized taxonomy information for Kubernetes.
Customers can also request suggestions for partially entered skill names.
Example:
Suggest valid skill names beginning with “Kuber.”
Using standardized skill information can improve data consistency across resumes, job descriptions, and recruitment systems.
Job Profile Taxonomy
Job Profile Taxonomy helps customers standardize and enrich job titles.
The returned information may include:
- Standardized job profile
- Description
- Job profile aliases
- Related job profiles
- Taxonomy classification
- O*NET or ESCO mappings, where available
Example:
Find the standardized job profile for “Backend Java Programmer.”
Users may also request autocomplete suggestions for a partial job title.
Example:
Suggest job profiles beginning with “Data Eng.”
Resume Redaction
Resume Redaction helps customers mask or remove selected personal information from a resume.
Depending on the configured options, redacted information may include:
- Candidate name
- Contact details
- Photograph
- Age-related information
- Other personally identifiable information
Example:
Anonymize this resume by removing the candidate’s name, contact information, photograph, and age-related details.
Resume redaction can support privacy-focused hiring processes and blind resume review.
Document Reformatting
Customers may use RChilli to reformat resume information using an available template.
Example:
Reformat this resume using the standard candidate profile template.
The available output format depends on the configured RChilli service and supported templates.
Document Format Conversion
Document conversion can be used to convert a supported document from one format to another.
Example:
Convert this resume into the supported output format.
Supported input and output formats depend on the configured document conversion service.
Named Entity Extraction
Named Entity Extraction identifies entities present in the submitted text.
These may include:
- People
- Organizations
- Locations
- Dates
- Job profiles
- Skills
- Other supported entity types
Example:
Extract the named entities from this resume text.
Contact Information Extraction
Customers can extract contact-related information from a resume or other submitted text.
Example:
Extract the candidate’s email address, telephone number, and location.
Location Geocoding
Location information can be enriched with standardized geographic data.
Depending on the available input and service configuration, the result may include:
- Standardized city
- State
- Country
- Geographic coordinates
- Other location information
Example:
Standardize and geocode the locations found in this resume.
Job-Zone Identification
RChilli can determine the applicable O*NET Job Zone for a job profile.
Job Zones represent the education, experience, and training generally required for a role.
Example:
Determine the Job Zone for a Data Scientist.
Capability Availability
Not every capability may be available in every customer environment.
Availability depends on:
- The customer’s RChilli subscription
- Enabled MCP tools
- RChilli account configuration
- Index availability
- Supported document formats
- AI client capabilities
- Access permissions
Customers should contact RChilli Support or their RChilli representative to confirm the services enabled for their account.
